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Figure.
Estimated Weights for the Weighted Quantile Sum (WQS) Regression Index
Estimated Weights for the Weighted Quantile Sum (WQS) Regression Index

A, Good micronutrients (Amyotrophic Lateral Sclerosis Functional Rating Scale–Revised [ALSFRS-R] score, positive β coefficient; P < .001; percentage forced vital capacity [FVC], positive β; P < .001). B, Good food groups (ALSFRS-R score, positive β; P = .001; percentage FVC, positive β; P = .001). C, Bad food groups (ALSFRS-R score, negative β; P = .002; percentage FVC, negative β; P = .29). D, Good vitamins and minerals (ALSFRS-R score, positive β; P = .02; percentage FVC, positive β; P = .02). The value indicates the estimated weights of each variable for the WQS regression index for the category. Blue indicates ALSFRS-R score and orange, percentage FVC.

Table 1.  
Dietary Intake in Patients With ALS
Dietary Intake in Patients With ALS
Table 2.  
Regression Analysis of Carotene and Antioxidant Indices and ALSFRS-R Score and Percentage FVC
Regression Analysis of Carotene and Antioxidant Indices and ALSFRS-R Score and Percentage FVC
Table 3.  
Weighted Quartile Sum Regression
Weighted Quartile Sum Regression
1.
Mehta  P, Antao  V, Kaye  W,  et al; Division of Toxicology and Human Health Sciences, Agency for Toxic Substances and Disease Registry, Atlanta, Georgia; Centers for Disease Control and Prevention (CDC).  Prevalence of amyotrophic lateral sclerosis - United States, 2010-2011.  MMWR Suppl. 2014;63(7):1-14.PubMedGoogle Scholar
2.
Mitsumoto  H, Chad  D, Pioro  E.  Amyotrophic Lateral Sclerosis. Vol 49. New York, NY: Oxford Press; 1997.
3.
Wicklund  MP.  Amyotrophic lateral sclerosis: possible role of environmental influences.  Neurol Clin. 2005;23(2):461-484.PubMedGoogle ScholarCrossref
4.
D’Amico  E, Factor-Litvak  P, Santella  RM, Mitsumoto  H.  Clinical perspective on oxidative stress in sporadic amyotrophic lateral sclerosis.  Free Radic Biol Med. 2013;65:509-527.PubMedGoogle ScholarCrossref
5.
Okamoto  K, Kihira  T, Kondo  T,  et al.  Nutritional status and risk of amyotrophic lateral sclerosis in Japan.  Amyotroph Lateral Scler. 2007;8(5):300-304.PubMedGoogle ScholarCrossref
6.
Nelson  LM, Matkin  C, Longstreth  WT  Jr, McGuire  V.  Population-based case-control study of amyotrophic lateral sclerosis in western Washington state, II: diet.  Am J Epidemiol. 2000;151(2):164-173.PubMedGoogle ScholarCrossref
7.
Longnecker  MP, Kamel  F, Umbach  DM,  et al.  Dietary intake of calcium, magnesium and antioxidants in relation to risk of amyotrophic lateral sclerosis.  Neuroepidemiology. 2000;19(4):210-216.PubMedGoogle ScholarCrossref
8.
Wang  H, O’Reilly  EJ, Weisskopf  MG,  et al.  Vitamin E intake and risk of amyotrophic lateral sclerosis: a pooled analysis of data from 5 prospective cohort studies.  Am J Epidemiol. 2011;173(6):595-602.PubMedGoogle ScholarCrossref
9.
Fitzgerald  KC, O’Reilly  EJ, Fondell  E,  et al.  Intakes of vitamin C and carotenoids and risk of amyotrophic lateral sclerosis: pooled results from 5 cohort studies.  Ann Neurol. 2012;73(2):236-245.PubMedGoogle ScholarCrossref
10.
Fondell  E, O’Reilly  EJ, Fitzgerald  KC,  et al.  Magnesium intake and risk of amyotrophic lateral sclerosis: results from five large cohort studies.  Amyotroph Lateral Scler Frontotemporal Degener. 2013;14(5-6):356-361.PubMedGoogle ScholarCrossref
11.
Ascherio  A, Weisskopf  MG, O’reilly  EJ,  et al.  Vitamin E intake and risk of amyotrophic lateral sclerosis.  Ann Neurol. 2005;57(1):104-110.PubMedGoogle ScholarCrossref
12.
Veldink  JH, Kalmijn  S, Groeneveld  GJ,  et al.  Intake of polyunsaturated fatty acids and vitamin E reduces the risk of developing amyotrophic lateral sclerosis.  J Neurol Neurosurg Psychiatry. 2007;78(4):367-371.PubMedGoogle ScholarCrossref
13.
Okamoto  K, Kihira  T, Kobashi  G,  et al.  Fruit and vegetable intake and risk of amyotrophic lateral sclerosis in Japan.  Neuroepidemiology. 2009;32(4):251-256.PubMedGoogle ScholarCrossref
14.
Fitzgerald  KC, O’Reilly  EJ, Falcone  GJ,  et al.  Dietary ω-3 polyunsaturated fatty acid intake and risk for amyotrophic lateral sclerosis.  JAMA Neurol. 2014;71(9):1102-1110.PubMedGoogle ScholarCrossref
15.
O’Reilly  EJ, Wang  H, Weisskopf  MG,  et al.  Premorbid body mass index and risk of amyotrophic lateral sclerosis.  Amyotroph Lateral Scler Frontotemporal Degener. 2013;14(3):205-211.PubMedGoogle ScholarCrossref
16.
Mohanty  P, Ghanim  H, Hamouda  W, Aljada  A, Garg  R, Dandona  P.  Both lipid and protein intakes stimulate increased generation of reactive oxygen species by polymorphonuclear leukocytes and mononuclear cells.  Am J Clin Nutr. 2002;75(4):767-772.PubMedGoogle Scholar
17.
Bloomer  RJ, Fisher-Wellman  KH.  Systemic oxidative stress is increased to a greater degree in young, obese women following consumption of a high fat meal.  Oxid Med Cell Longev. 2009;2(1):19-25.PubMedGoogle ScholarCrossref
18.
Bloomer  RJ, Kabir  MM, Marshall  KE, Canale  RE, Farney  TM.  Postprandial oxidative stress in response to dextrose and lipid meals of differing size.  Lipids Health Dis. 2010;9:79.PubMedGoogle ScholarCrossref
19.
McCarthy  CG, Farney  TM, Canale  RE, Dessoulavy  ME, Bloomer  RJ.  High-fat feeding, but not strenuous exercise, increases blood oxidative stress in trained men.  Appl Physiol Nutr Metab. 2013;38(1):33-41.PubMedGoogle ScholarCrossref
20.
Sies  H, Stahl  W, Sevanian  A.  Nutritional, dietary and postprandial oxidative stress.  J Nutr. 2005;135(5):969-972.PubMedGoogle Scholar
21.
Cedarbaum  JM, Stambler  N, Malta  E,  et al; BDNF ALS Study Group (Phase III).  The ALSFRS-R: a revised ALS functional rating scale that incorporates assessments of respiratory function.  J Neurol Sci. 1999;169(1-2):13-21.PubMedGoogle ScholarCrossref
22.
Brooks  BR, Miller  RG, Swash  M, Munsat  TL; World Federation of Neurology Research Group on Motor Neuron Diseases.  El Escorial revisited: revised criteria for the diagnosis of amyotrophic lateral sclerosis.  Amyotroph Lateral Scler Other Motor Neuron Disord. 2000;1(5):293-299.PubMedGoogle ScholarCrossref
23.
de Carvalho  M, Dengler  R, Eisen  A,  et al.  The Awaji criteria for diagnosis of ALS.  Muscle Nerve. 2011;44(3):456-457.PubMedGoogle ScholarCrossref
24.
Mitsumoto  H, Factor-Litvak  P, Andrews  H,  et al; ALS COSMOS Study Group.  ALS Multicenter Cohort Study of Oxidative Stress (ALS COSMOS): study methodology, recruitment, and baseline demographic and disease characteristics.  Amyotroph Lateral Scler Frontotemporal Degener. 2014;15(3-4):192-203.PubMedGoogle ScholarCrossref
25.
Mitsumoto  H, Brooks  BR, Silani  V.  Clinical trials in amyotrophic lateral sclerosis: why so many negative trials and how can trials be improved?  Lancet Neurol. 2014;13(11):1127-1138.PubMedGoogle ScholarCrossref
26.
Kaufmann  P, Levy  G, Thompson  JL,  et al.  The ALSFRSr predicts survival time in an ALS clinic population.  Neurology. 2005;64(1):38-43.PubMedGoogle ScholarCrossref
27.
Gordon  PH, Miller  RG, Moore  DH.  ALSFRS-R.  Amyotroph Lateral Scler Other Motor Neuron Disord. 2004;5(suppl 1):90-93.PubMedGoogle ScholarCrossref
28.
Elamin  M, Bede  P, Montuschi  A, Pender  N, Chio  A, Hardiman  O.  Predicting prognosis in amyotrophic lateral sclerosis: a simple algorithm.  J Neurol. 2015;262(6):1447-1454.PubMedGoogle ScholarCrossref
29.
Block  G, Hartman  AM, Naughton  D.  A reduced dietary questionnaire: development and validation.  Epidemiology. 1990;1(1):58-64.PubMedGoogle ScholarCrossref
30.
Cummings  SR, Block  G, McHenry  K, Baron  RB.  Evaluation of two food frequency methods of measuring dietary calcium intake.  Am J Epidemiol. 1987;126(5):796-802.PubMedGoogle Scholar
31.
Nieves  JW, Golden  AL, Siris  E, Kelsey  JL, Lindsay  R.  Teenage and current calcium intake are related to bone mineral density of the hip and forearm in women aged 30-39 years.  Am J Epidemiol. 1995;141(4):342-351.PubMedGoogle ScholarCrossref
32.
Serdula  M, Coates  R, Byers  T,  et al.  Evaluation of a brief telephone questionnaire to estimate fruit and vegetable consumption in diverse study populations.  Epidemiology. 1993;4(5):455-463.PubMedGoogle ScholarCrossref
33.
Willett  W.  Nutritional Epidemiology. New York, NY: Oxford University Press; 1989:416.
34.
NutritionQuest. http://www.nutritionquest.com. Accessed September 16, 2016.
35.
Yorita Christensen  KL, Carrico  CK, Sanyal  AJ, Gennings  C.  Multiple classes of environmental chemicals are associated with liver disease: NHANES 2003-2004.  Int J Hyg Environ Health. 2013;216(6):703-709.PubMedGoogle ScholarCrossref
36.
Carrico  C, Gennings  C, Wheeler  DC, Factor-Litvak  P.  Characterization of weighted quantile sum regression for highly correlated data in a risk analysis setting.  J Agric Biol Environ Stat. 2015;20(1):100-120. doi:10.1007/s13253-014-0180-3Google ScholarCrossref
37.
Mahabir  S, Baer  DJ, Giffen  C,  et al.  Calorie intake misreporting by diet record and food frequency questionnaire compared to doubly labeled water among postmenopausal women.  Eur J Clin Nutr. 2006;60(4):561-565.PubMedGoogle ScholarCrossref
38.
Dorst  J, Kühnlein  P, Hendrich  C, Kassubek  J, Sperfeld  AD, Ludolph  AC.  Patients with elevated triglyceride and cholesterol serum levels have a prolonged survival in amyotrophic lateral sclerosis.  J Neurol. 2011;258(4):613-617.PubMedGoogle ScholarCrossref
39.
Zhang  W, Li  P, Hu  X, Zhang  F, Chen  J, Gao  Y.  Omega-3 polyunsaturated fatty acids in the brain: metabolism and neuroprotection.  Front Biosci (Landmark Ed). 2011;16:2653-2670.PubMedGoogle ScholarCrossref
40.
Paganoni  S, Deng  J, Jaffa  M, Cudkowicz  ME, Wills  A-M.  Body mass index, not dyslipidemia, is an independent predictor of survival in amyotrophic lateral sclerosis.  Muscle Nerve. 2011;44(1):20-24.PubMedGoogle ScholarCrossref
41.
Swash  M.  Diet and risk of amyotrophic lateral sclerosis: is lifestyle important?  JAMA Neurol. 2014;71(9):1085-1086.PubMedGoogle ScholarCrossref
42.
Silva  LB, Mourão  LF, Silva  AA,  et al.  Effect of nutritional supplementation with milk whey proteins in amyotrophic lateral sclerosis patients.  Arq Neuropsiquiatr. 2010;68(2):263-268.PubMedGoogle ScholarCrossref
Original Investigation
December 2016

Association Between Dietary Intake and Function in Amyotrophic Lateral Sclerosis

Author Affiliations
  • 1Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York
  • 2Clinical Research Center, Helen Hayes Hospital, West Haverstraw, New York
  • 3Department of Preventive Medicine, Icahn School of Medicine at Mount Sinai, New York, New York
  • 4Department of Neurology, Columbia University, New York, New York
  • 5Department of Neurology, University of California–Davis, Sacramento
  • 6Department of Neurological Sciences, University of Nebraska Medical Center, Omaha
  • 7Department of Neurology, Mayo Clinic, Rochester, Minnesota
  • 8Neurological Institute, Catania, Italy
  • 9Department of Psychiatry, New York State Psychiatric Institute, New York
 

Copyright 2016 American Medical Association. All Rights Reserved.

JAMA Neurol. 2016;73(12):1425-1432. doi:10.1001/jamaneurol.2016.3401
Key Points

Question  What is the association between nutrient intake and amyotrophic lateral sclerosis function and respiratory function at diagnosis?

Findings  In this cross-sectional analysis of a multicenter cohort of 302 patients with amyotrophic lateral sclerosis, antioxidants, carotenes, fruits, and vegetables were associated with higher amyotrophic lateral sclerosis function at baseline.

Meaning  Nutritional care of the patient with amyotrophic lateral sclerosis should include promotion of foods high in antioxidants and carotenes, including fruits and vegetables.

Abstract

Importance  There is growing interest in the role of nutrition in the pathogenesis and progression of amyotrophic lateral sclerosis (ALS).

Objective  To evaluate the associations between nutrients, individually and in groups, and ALS function and respiratory function at diagnosis.

Design, Setting, and Participants  A cross-sectional baseline analysis of the Amyotrophic Lateral Sclerosis Multicenter Cohort Study of Oxidative Stress study was conducted from March 14, 2008, to February 27, 2013, at 16 ALS clinics throughout the United States among 302 patients with ALS symptom duration of 18 months or less.

Exposures  Nutrient intake, measured using a modified Block Food Frequency Questionnaire (FFQ).

Main Outcomes and Measures  Amyotrophic lateral sclerosis function, measured using the ALS Functional Rating Scale–Revised (ALSFRS-R), and respiratory function, measured using percentage of predicted forced vital capacity (FVC).

Results  Baseline data were available on 302 patients with ALS (median age, 63.2 years [interquartile range, 55.5-68.0 years]; 178 men and 124 women). Regression analysis of nutrients found that higher intakes of antioxidants and carotenes from vegetables were associated with higher ALSFRS-R scores or percentage FVC. Empirically weighted indices using the weighted quantile sum regression method of “good” micronutrients and “good” food groups were positively associated with ALSFRS-R scores (β [SE], 2.7 [0.69] and 2.9 [0.9], respectively) and percentage FVC (β [SE], 12.1 [2.8] and 11.5 [3.4], respectively) (all P < .001). Positive and significant associations with ALSFRS-R scores (β [SE], 1.5 [0.61]; P = .02) and percentage FVC (β [SE], 5.2 [2.2]; P = .02) for selected vitamins were found in exploratory analyses.

Conclusions and Relevance  Antioxidants, carotenes, fruits, and vegetables were associated with higher ALS function at baseline by regression of nutrient indices and weighted quantile sum regression analysis. We also demonstrated the usefulness of the weighted quantile sum regression method in the evaluation of diet. Those responsible for nutritional care of the patient with ALS should consider promoting fruit and vegetable intake since they are high in antioxidants and carotenes.

Introduction

Amyotrophic lateral sclerosis (ALS) is a severe neurodegenerative disorder that causes progressive muscle atrophy, paralysis, and eventual respiratory failure. The incidence rate of ALS ranges from 1.5 to 2.5 per 100 000 individuals per year, with a prevalence rate of approximately 3.9 to 8 per 100 000 individuals in the United States.1 Males are slightly more affected than females, with a ratio of approximately 1.6:1. The median survival time from onset of ALS ranges from 20 to 48 months, but 10% to 20% of patients survive longer than 10 years.2 There is growing interest in the role of nutrition and environmental factors in the pathogenesis and progression of ALS.3,4 There is some evidence that risk of ALS increases with increased intake of macronutrients, such as carbohydrates, glutamate, and fat, and with low intake of various micronutrients, including vitamin E, ω-3 polyunsaturated fatty acids, and carotenoids, as well as fruits and vegetables, although this risk is not consistently demonstrated in studies.5-13 In a recent analysis of data pooled from 5 cohort studies with a total of 995 patients with ALS, the highest intake of ω-3 polyunsaturated fatty acids as compared with the lowest intake was associated with a 34% reduced risk of ALS.14 Risk of ALS is also inversely associated with body mass index (BMI).15

Previous research suggests that oxidative stress is associated with the pathogenesis of ALS; there is some evidence that dietary factors may increase5,6,16-20 or potentially decrease5-14 oxidative stress. Previous studies have not evaluated whether nutrients or foods are associated with ALS or respiratory function soon after diagnosis. Using data from a study of ALS progression, our analysis examines associations between nutritional intake and functional performance (measured by ALS Functional Rating Scale–Revised [ALSFRS-R]21 scores) and respiratory function (measured as forced vital capacity [FVC]) at the time of study entry.

Methods

Patients diagnosed with ALS based on revised El Escorial22 or Awaji23 criteria less than 18 months after symptom onset were recruited into the longitudinal ALS Multicenter Cohort Study of Oxidative Stress (ALS COSMOS) study from March 14, 2008, to February 27, 2013, at 16 clinical centers located throughout the United States. Detailed description of patients and methods were previously reported.24 This study is a cross-sectional analysis of baseline data.

The procedures followed were in accordance with the ethical standards of each institutional review board where approval was obtained for each of the 16 clinical sites. Written consent was provided where possible and if the patient was unable to provide written consent, verbal consent with an independent witness was obtained.

Demographic and Neurologic Data

Clinical assessment included height, weight, scores on the ALSFRS-R using a 12-item questionnaire, percentage FVC, and a comprehensive neurologic examination. The ALSFRS-R is the most widely used clinical outcome in ALS clinical trials25 and has been extensively validated.26-28

Dietary Data

To assess diet, we used a modification of the previously validated Food Frequency Questionnaire (FFQ),29-32 which entailed shortening the questionnaire from 127 to 85 items so that completion time would be approximately 15 minutes, similar to previously validated FFQs. Food frequency questionnaires are preferred to assess usual dietary intakes.33 Our shortened FFQ assessed specific intake information, focusing on foods and nutrients considered to be antioxidants; vitamins A, C, and E; β-carotene; calcium; iron; zinc; and selenium. In addition to the 85 questions, there was an open-ended section on additional foods consumed, 10 summary questions, and 19 questions about supplement intake. Participants self-administered the FFQ, with caregiver assistance if needed. All completed FFQ forms were scanned by Nutritionquest,34 which converted FFQ data into estimates of average daily nutrient intake using a standardized reference nutrient database and provided food-specific and food group intake data.

Given that antioxidants may be particularly important, we a priori estimated a carotene index, which was a sum of tertile groupings (low, 1; moderate, 2; and high, 3) of α-carotene, β-carotene, cryptoxanthin, lutein and zeaxanthin, and lycopene. The a priori antioxidant index included these nutrients as well as similar tertile groupings of vitamin C, vitamin E, selenium, and quercetin. We administered the survey twice to 29 patients with ALS and there were no differences in the nutrients of interest between the results of first and second FFQ (Wilcoxon signed rank test). The intraclass correlation coefficients ranged from 0.62 to 0.87 for all nutrients analyzed, except for lycopene (r = 0.35).

Groups of Variables

Nutrients and food groups were grouped for further analysis based on their anticipated association with ALS function (from a review of the literature); items were primarily grouped as “good” if they had antioxidant properties or were previously associated with reduced risk of ALS5-14 or as “bad” based on association with oxidative stress or increased risk of ALS.5,6,16-20 Micronutrients considered potentially good were vitamin C; vitamin E; α-carotene; β-carotene; cryptoxanthin; lutein and zeaxanthin; selenium; lycopene; quercetin; ω-3 fatty acids; isoflavones; cysteine; vitamin A; vitamin D; fiber from beans, vegetables, and fruit, and grains; and ω-6 fatty acids. Micronutrients considered potentially bad were trans-fat, saturated fats, ω-6 fatty acids, total sugars, high ratio of ω-6 to ω-3 fatty acids, and methionine. Macronutrients considered potentially good were food energy (calories), protein, and carbohydrates; macronutrients considered potentially bad were dietary fat and sugary beverages. Food groups considered potentially good were whole grains; milk; yogurt; solid fruits; fruit juice; legumes; eggs; fish high in ω-3 fatty acids; fish low in ω-3 fatty acids; poultry; soy foods; protein from nuts and seeds; beneficial oils (from fish, nuts, avocado, and dressing); deep yellow, orange, and dark green vegetables; other vegetables (not dark green, yellow, or orange); potatoes; and tomatoes. Food groups considered potentially bad were oils, sweets, sodas, cheese, milk, eggs, beef, pork, lamb, and lunch meats.

In addition, exploratory analyses were performed on a series of nutrients considered potentially good (calcium, iron, potassium, thiamin, riboflavin, niacin, vitamin C, vitamin E, zinc, vitamin B6, magnesium, retinol, vitamin D [in micrograms], vitamin K, selenium, and total glutathione) vs nutrients considered potentially bad (phosphorous, sodium, caffeine, and foods resulting in a high glycemic index). The use of groups of nutrients and foods allows examination of nutrients that are highly correlated based on the dietary patterns of individuals. Moreover, our weighted quantile sum (WQS) regression method, described below, ensures that nutrients that are grouped incorrectly will have a smaller weight in the proposed groupings. Thus, we were able to simultaneously examine nutrients instead of relying on examining individual nutrients, which is a less optimal method and more prone to type I error.

Statistical Analysis

All statistical models used ALSFRS-R score or percentage FVC as the outcome variables. We included covariates if the association (estimated β coefficient) changed by 10% comparing models with and without the covariates. Thus, our final models included age, sex, current BMI, duration of symptoms, and caloric intake. Regression analysis was performed using the carotene index and antioxidant index as the primary exposures.

We also used WQS regression35,36 to account for the colinearity between nutrient exposures. Briefly, nutrients and food groups were grouped a priori. For each food grouping, WQS regression resulted in an empirically weighted sum of the quartiles of the food group components. Each WQS regression index was included in a regression model, adjusted for covariates. The corresponding weights were used to identify important components when the regression coefficient of the index was significant. The WQS regression method is robust against improper assignment of a nutrient or food type as good or bad since that nutrient or food will be assigned a negligible weight, minimizing potential error in nutrient grouping.

Results

A total of 355 patients were eligible and enrolled in ALS COMOS, while 477 potentially eligible but nonenrolled patients were reported by the sites. Major reasons for exclusion were that the study was not discussed (253 [53%]), patients refused to participate (143 [30%]), or patients were overwhelmed with their diagnosis (38 [8%]).24 There were no differences between those enrolled and those not enrolled on demographics (eg, age, sex, and race/ethnicity), duration of disease, El Escorial Criteria diagnostic groups, participation in clinical trials, and use of alternative treatments; however, enrolled patients were more likely to have private insurance and less likely to be covered by Medicare compared with those who were not enrolled.24 A total of 53 patients did not have ALSFRS-R performed or FVC measured or nutrition data were not available, leaving 302 patients for this analysis. These 302 patients (178 men [58.9%]) had a median age of 63.2 years (interquartile range [IQR], 55.5-68.0 years), median BMI (calculated as weight in kilograms divided by height in meters squared) of 26 (IQR, 23.5-28.5), and median symptom duration of 0.94 year (IQR, 0.65-1.25 years). At the baseline visit, approximately half of the patients reported eating problems early in the course of the disease and occasional choking. Two hundred sixteen patients (71.5%) had a spinal onset of disease and 85 (27.7%) had bulbar onset. The median ALSFRS-R score was 37 (IQR, 33-41), reflecting modestly severe ALS, and median FVC was 82% (IQR, 66%-97%), reflecting low normal respiratory function. Higher ALSFRS-R scores and higher percentage of FVC indicate better function.

The mean (SD) daily total calorie intake was 1730 (747); mean daily intake of other nutrients is listed in Table 1. There was no significant difference in caloric intake between those who reported eating problems early in the course of the disease and occasional choking at the baseline visit (1827 calories per day) compared with those who did not report such problems (1692 calories per day).

After controlling for age, sex, duration of symptoms, current BMI, and caloric intake, the antioxidant index and carotene index were positively associated with ALSFRS-R score (β [SE], 0.182 [0.093]; P = .05 and β [SE], 0.303 [0.193]; P = .03, respectively) and with percentage FVC (β [SE], 0.773 [0.325]; P = .02 and β [SE], 1.08 [0.486]; P = .03, respectively; Table 2). There was no significant difference between the results of the antioxidant and carotene indices and ALSFRS-R score or percentage FVC based on whether patients reported eating problems early in the course of the disease and occasional choking at the baseline visit.

Regression analysis for individual nutrients and ALSFRS-R score and percentage FVC after controlling for age, sex, current BMI, duration of symptoms, and dietary caloric intake value of individual nutrients can be found in the eTable in the Supplement. Because there are strong correlations between these individual nutrients (r = 0.40-0.96; P < .01), it is not possible to determine the actual nutrients with the strongest associations; therefore, WQS regression analysis was used.

Table 3 shows the direction of the β coefficient and P values for WQS regression analyses. Detailed results from this analysis are described below and in the Figure, which illustrates the estimated weights of each variable for the WQS regression index for each nutrient or food, with larger weights indicating a stronger contribution to the index.

Micronutrients and Macronutrients

An empirical WQS regression index of good micronutrients was positively associated with ALSFRS-R score (β [SE], 2.7 [0.69]; P < .001), with 91% of the weight associated with 9 of 18 nutrients (Table 3 and Figure, A). Similarly, the WQS regression for good micronutrients associated with percentage FVC was positive (β [SE], 12.1 [2.8]; P < .001) (Table 3); however, 80% of the weights were concentrated on 6 nutrients (lycopene, ω-3 fatty acids, ω-6 fatty acids, isoflavones, and fiber from both vegetables and grains) (Figure, A).

The empirical WQS regression indices developed for bad micronutrients were not significantly associated with either outcome variable. The empirical WQS regression indices developed for macronutrients were not significantly associated with ALSFRS-R score or percentage FVC (Table 3).

Food Groups

An empirical WQS regression index of good food groups was positively associated with ALSFRS-R score (β [SE], 2.9 [0.9]; P = .001) (Table 3), with 71% of the weight associated with fruit, eggs, fish, poultry, nuts and seeds, beneficial oils, and other vegetables (Figure, B). The WQS regression index of good food groups was also positively associated with percentage FVC (β [SE], 11.5 [3.4]; P < .001) (Table 3), with weights similar to those for ALSFRS-R: yogurt, fruits, fish, poultry, nuts and seeds, beneficial oils, and other vegetables (Figure, B).

The empirical WQS regression index of bad food groups was negatively and significantly associated with ALSFRS-R score (β [SE], –1.6 [0.53]; P = .002) (Table 3). The primary component was milk, with 50% of the weight, as well as beef and pork (11%) and lunch meats (32%) (Figure, C). There was no association with percentage FVC.

Exploratory Analyses With WQS Regression

When selected beneficial vitamins and minerals were considered, the WQS regression index had a positive and significant association with ALSFRS-R score (β [SE], 1.5 [0.61]; P = .02). Five vitamins held 95% of the weight (niacin, vitamin B6, vitamin K, selenium, and glutathione). A similar WQS regression index was positive and significantly associated with percentage FVC (β [SE], 5.2 [2.2]; P = .02), with 85% of the weight from vitamin B6, riboflavin, vitamin E, vitamin K, and glutathione.

Discussion

In the longitudinal ALS COSMOS study, we analyzed the cross-sectional data of dietary variables and ALS function at baseline (as ALSFRS-R score and percentage FVC). Our results indicate that greater intakes of antioxidant nutrients and foods high in carotenoids appear to be associated with better function at study entry. Weighted quantile sum regression allows for the analysis of combinations of nutrients and food groups compared with the typical evaluation of single nutrients that cannot be performed owing to strong collinearity between all nutrients. Weighted quantile sum regression determines an empirically weighted quantile sum index associating a set of nutrients with specific outcome variables, in this case ALSFRS-R score and percentage FVC. The 2 most highly weighted micronutrients associated with ALSFRS-R score were nutrients believed to be strong antioxidants: lutein and zeaxanthin (15%) and ω-3 fatty acids (18%); the dominant components associated with percentage FVC were ω-3 fatty acids (19%), ω-6 fatty acids (23%), and fiber from grains and vegetables and fruit (9% and 14%, respectively). The primary components from the analyses of the good food group were eggs (19% associated with with ALSFRS-R score), fish, poultry, beneficial oils, and vegetables. These foods supply antioxidants and are typically associated with a healthy diet. On the other hand, milk (50%) and lunch meats (32%) were highly weighted in a negative association with ALSFRS-R score, perhaps a result of the higher fat intake and the potential for these foods to promote oxidative stress.

There were some limitations in this study and only associations, not cause and effect, can be found in this cross-sectional analysis. Ideally, WQS regression is performed on 2 independent data sets—one to build the WQS regression index through bootstrap sampling, and the second to test the significance of the signal from the created index. In our analysis, the sample size of 302 was not considered large enough to split the data into a discovery data set and a validation data set. Therefore, weights were estimated in the same data used to test for significance. In addition, data were collected with an FFQ as an attempt to measure dietary habits over time, but this method may not always represent true daily diets. Although the caloric intake may be slightly underreported with the use of an FFQ,37 the ranking of caloric and nutrient intake will be accurate. There are only limited data on which nutrients are associated with the development of ALS or are associated with progression of ALS. Our groupings of good and bad foods and nutrients were based on existing knowledge of ALS and general dietary knowledge.5-14,16-20 However, if we incorrectly assigned a nutrient or food type to a nutrient group, it will have a very small weight in the WQS regression, minimizing the error from nutrient grouping.

A strength of this study was the relatively large sample size of patients with ALS who appear representative of all eligible patients at the ALS centers, improving generalizability. To our knowledge, this is also one of the first studies to evaluate diet in association with measures of ALS function near the time of diagnosis. The consistency of the findings using 2 different statistical methods adds strength. Although we used cross-sectional data for this analysis, we intend to include the 24-month data on both dietary intake and progression of ALS in future analyses when those data are available. Longitudinal data will be important to confirm any findings from this study as well as to evaluate the role of nutrition in the progression of ALS.

Several nutrients have been proposed to be associated with the development of ALS, although the data are largely inconsistent.5-11,13,14,38 Fitzgerald et al14 suggested that fatty acid composition of cell plasma membranes might modulate oxidative stress responses, excitotoxicity, and inflammation, factors hypothesized to be associated with ALS.39 Polyunsaturated fatty acid intake may also be associated with body fat, which also appears to protect against ALS.40,41

We found that milk intake may have a negative affect on ALS function (assessed by ALSFRS-R score and percentage FVC) at study entry. Milk-based supplements are used for patients with ALS and were reported to lead to weight gain, improved biochemistry, and a slower decline in ALSFRS-R score based on a 4-month study of only 16 patients with ALS.42 It will be important to see how dairy and milk intake are associated with changes in ALSFRS-R score and mortality in the longitudinal follow-up of the ALS COSMOS population.

Although previous studies have associated the intake of several healthy nutrients and foods with reduced risk of ALS,4-13 for the first time, to our knowledge, we have shown that healthy nutrients and antioxidants are associated with better ALS function around the time of diagnosis. Therefore, nutritional care of the patient with ALS might include not only caloric management but also promotion of fruit and vegetable intake.

Conclusions

Evaluation of baseline dietary intake and severity of ALS (assessed by percentage FVC and ALSFRS-R score) indicates a consistent association between these variables and certain nutrients. Antioxidant nutrients, foods high in carotenoids and fiber, and vegetable intake are associated with better ALS function using 2 different analysis methods.

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Article Information

Accepted for Publication: July 12, 2016.

Corresponding Author: Jeri W. Nieves, PhD, Department of Epidemiology, Mailman School of Public Health, Columbia University, 630 W 168th St, Ste PH 15-12, New York, NY 10032 (jwn5@cumc.columbia.edu).

Published Online: October 24, 2016. doi:10.1001/jamaneurol.2016.3401

Author Contributions: Drs Nieves and Mitsumoto had full access to all the data in the study and take full responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Nieves, Factor-Litvak, Sorenson, Mitsumoto.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Nieves, Gennings, Factor-Litvak, Hupf, Sharf, Sorenson.

Critical revision of the manuscript for important intellectual content: Nieves, Factor-Litvak, Singleton, Oskarsson, Fernandes Filho, Sorenson, D’Amico, Goetz, Mitsumoto.

Statistical analysis: Nieves, Gennings, Factor-Litvak, Sharf, Goetz.

Obtained funding: Factor-Litvak, Mitsumoto.

Administrative, technical, or material support: Nieves, Hupf, Singleton, Oskarsson, Sorenson, Mitsumoto.

Study supervision: Factor-Litvak, Hupf, Singleton, Oskarsson, Sorenson, Mitsumoto.

Conflict of Interest Disclosures: Dr Mitsumoto reported receiving research support from the Centers for Disease Control and Prevention, the Agency for Toxic Substances and Disease Registry, Office of Rare Diseases, Muscular Dystrophy Association Wings Over Wall Street, National Institute of Neurological Disorders and Stroke, the Muscular Dystrophy Association, the Amyotrophic Lateral Sclerosis Association, Motor Neurone Disease Association, Amyotrophic Lateral Sclerosis Canada, Japan Amyotrophic Lateral Sclerosis Association, Amyotrophic Lateral Sclerosis Hope Foundation, Adams Foundation, International Amyotrophic Lateral Sclerosis Alliance, Cytokinetics, Biogen, Mitsubishi-Tanabe, and Dainippon-Sumitomo, as well as a conference grant from the International Amyotrophic Lateral Sclerosis Clinical Trial Guidelines Workshop. Dr Mitsumoto reported participating in clinical trials for Cytokinetics, serving on the Scientific Advisory Boards for Cytokinetics and Mitsubishi-Tanabe, and serving as a medical consultant for Advanced Medical. Dr Oskarsson reported receiving grants UL1 TR000002 and KL2 TR000134 from the National Institutes of Health. Dr D’Amico reported receiving editorial fees from Bayer Schering and Serono. No other disclosures were reported.

Funding/Support: Grant R01ES016348 from the National Institute of Environmental Health Sciences, National Institutes of Health, funded the entire study and the Muscular Dystrophy Association funded an earlier study that was incorporated into the Amyotrophic Lateral Sclerosis Multicenter Cohort Study of Oxidative Stress. Muscular Dystrophy Association Wings Over Wall Street, The Judith and Jean Pape Adams Charitable Foundation, and Ride for Life also supported part of the study.

Role of the Funder/Sponsor: The funding sources had no role in the design and conduct of the study; collection, management, analysis, or interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Group Information: The Amyotrophic Lateral Sclerosis Multicenter Cohort Study of Oxidative Stress (ALS COSMOS) Study Group includes Hiroshi Mitsumoto, MD, DSc, Jonathan Hupf, BA, Jess Singleton, BA, Christa Campanella Beck, BS, David Merle, BS, Tejal Shah, BS, Meredith Pasmantier Kim, BA, Yei-Won Lee, BA, Georgia Christodoulou, MA, Kate Dalton, MS, RD, Jessica Kidd, BA, Erin Gilbert, BA, and Mary Kilty, MBA, MPH (Columbia University Coordinating Center, New York, New York); Daragh Heitzman, MD, FAAN, Wendy Rodriguez, NRCMA, Shari Hand, BS, CCRC, Michelle Washington, NRCMA, Brent Spears, BS, CCRC, and Brandie Burson, NRCMA (Texas Neurology, PA, Dallas); Richard S. Bedlack, MD, PhD, MS, Karen Grace, RN, BSN, and Candace Boyette, RN, FNP (Duke University, Durham, North Carolina); Jonathan S. Katz, MD, Robert G. Miller, MD, Dallas Forshew, RN, BSN, Joni Beemsterboer, MPH, Will Harris, BA, Shelley McCoy, BS, Thaïs Zayas-Bazan, BA, and Chow Saephanh, BA (California Pacific Medical Center, San Francisco); Richard J. Barohn, MD, April L. McVey, MD, Mazen M. Dimachkie, MD, Mamatha Pasnoor, MD, Yunxia Wang, MD, Maureen Walsh, BS, Laura Herbelin, BS, CCRP, JoAnn Miller, BS, and Kristy Anderson, BS (University of Kansas, Kansas City); Eric J. Sorenson, MD, Sherry Klingerman, CCRP, and Delana Weis, LPN, CCRP (Mayo Clinic, Rochester, Minnesota); Björn Oskarsson, MD, Nanette Joyce, DO, MAS, Steffany Lim, BS, CCRP, and Michelle Cregan, CRA (University of California, Davis, Sacramento); Edward J. Kasarskis, MD, PhD, Kathie Vanderpool, RN, BS, Deborah Taylor, MS, Samantha Thomas, MS, Jason King, MS, and Robert Wells, CCRP (University of Kentucky, Lexington); Catherine Lomen-Hoerth, MD, PhD, Jennifer Murphy, PhD, Y-Nhy Duong, BA, Dennis Robins, BA, and Claudia Villerme, MEd (University of California, San Francisco); Yvonne D. Rollins, MD, PhD, Steven P. Ringel, MD, Dianna Quan, MD, and Elizabeth Whitethorn, BS (University of Colorado, Aurora); Tahseen Mozaffar, MD, PhD, Annabel K. Wang, MD, Veronica Martin, BA, Brian Minton, BS, BA, Patricia Tully, FNP, and Denise Davis, MPT (University of California, Irvine, Orange); J. Americo M. Fernandes Filho, MD, Pariwat Thaisetthawatkul, MD, Cindy Cowardin, RN, BSN, CCRP, and Russell Herstein, BA (University of Nebraska Medical Center, Omaha); Andrea J. Swenson, MD, Decontee Jimmeh-Fletcher, MD, Heena Olalde, RN, MSN, and Jeri Sieren, RN (University of Iowa, Iowa City); Sharon P. Nations, MD, Jeffrey Elliott, MD, Jaya Trivedi, MD, and Nina Gorham, CCRP (University of Texas–Southwestern, Dallas); Jeremy M. Shefner, MD, PhD, Mary Lou Watson, BA, RRT, CCRP, Jennifer Moore, Katie Markis, BA, CCRP, and Megan Grosso, RPA-C, DPT, PT (SUNY–Upstate Medical University, Syracuse, New York); and Jinsy A. Andrews, MD, MS, Agnes Koczon-Jaremko, MD, and Janet Bowen, BA, CRT (Hospital for Special Care, New Britain, Connecticut).

Additional Contributions: We are grateful for the patients and their families who enthusiastically participated in this labor-intensive study. Annette Kirshner, PhD, National Institute of Environmental Health Sciences, provided advice and support. She was not compensated for her contribution.

References
1.
Mehta  P, Antao  V, Kaye  W,  et al; Division of Toxicology and Human Health Sciences, Agency for Toxic Substances and Disease Registry, Atlanta, Georgia; Centers for Disease Control and Prevention (CDC).  Prevalence of amyotrophic lateral sclerosis - United States, 2010-2011.  MMWR Suppl. 2014;63(7):1-14.PubMedGoogle Scholar
2.
Mitsumoto  H, Chad  D, Pioro  E.  Amyotrophic Lateral Sclerosis. Vol 49. New York, NY: Oxford Press; 1997.
3.
Wicklund  MP.  Amyotrophic lateral sclerosis: possible role of environmental influences.  Neurol Clin. 2005;23(2):461-484.PubMedGoogle ScholarCrossref
4.
D’Amico  E, Factor-Litvak  P, Santella  RM, Mitsumoto  H.  Clinical perspective on oxidative stress in sporadic amyotrophic lateral sclerosis.  Free Radic Biol Med. 2013;65:509-527.PubMedGoogle ScholarCrossref
5.
Okamoto  K, Kihira  T, Kondo  T,  et al.  Nutritional status and risk of amyotrophic lateral sclerosis in Japan.  Amyotroph Lateral Scler. 2007;8(5):300-304.PubMedGoogle ScholarCrossref
6.
Nelson  LM, Matkin  C, Longstreth  WT  Jr, McGuire  V.  Population-based case-control study of amyotrophic lateral sclerosis in western Washington state, II: diet.  Am J Epidemiol. 2000;151(2):164-173.PubMedGoogle ScholarCrossref
7.
Longnecker  MP, Kamel  F, Umbach  DM,  et al.  Dietary intake of calcium, magnesium and antioxidants in relation to risk of amyotrophic lateral sclerosis.  Neuroepidemiology. 2000;19(4):210-216.PubMedGoogle ScholarCrossref
8.
Wang  H, O’Reilly  EJ, Weisskopf  MG,  et al.  Vitamin E intake and risk of amyotrophic lateral sclerosis: a pooled analysis of data from 5 prospective cohort studies.  Am J Epidemiol. 2011;173(6):595-602.PubMedGoogle ScholarCrossref
9.
Fitzgerald  KC, O’Reilly  EJ, Fondell  E,  et al.  Intakes of vitamin C and carotenoids and risk of amyotrophic lateral sclerosis: pooled results from 5 cohort studies.  Ann Neurol. 2012;73(2):236-245.PubMedGoogle ScholarCrossref
10.
Fondell  E, O’Reilly  EJ, Fitzgerald  KC,  et al.  Magnesium intake and risk of amyotrophic lateral sclerosis: results from five large cohort studies.  Amyotroph Lateral Scler Frontotemporal Degener. 2013;14(5-6):356-361.PubMedGoogle ScholarCrossref
11.
Ascherio  A, Weisskopf  MG, O’reilly  EJ,  et al.  Vitamin E intake and risk of amyotrophic lateral sclerosis.  Ann Neurol. 2005;57(1):104-110.PubMedGoogle ScholarCrossref
12.
Veldink  JH, Kalmijn  S, Groeneveld  GJ,  et al.  Intake of polyunsaturated fatty acids and vitamin E reduces the risk of developing amyotrophic lateral sclerosis.  J Neurol Neurosurg Psychiatry. 2007;78(4):367-371.PubMedGoogle ScholarCrossref
13.
Okamoto  K, Kihira  T, Kobashi  G,  et al.  Fruit and vegetable intake and risk of amyotrophic lateral sclerosis in Japan.  Neuroepidemiology. 2009;32(4):251-256.PubMedGoogle ScholarCrossref
14.
Fitzgerald  KC, O’Reilly  EJ, Falcone  GJ,  et al.  Dietary ω-3 polyunsaturated fatty acid intake and risk for amyotrophic lateral sclerosis.  JAMA Neurol. 2014;71(9):1102-1110.PubMedGoogle ScholarCrossref
15.
O’Reilly  EJ, Wang  H, Weisskopf  MG,  et al.  Premorbid body mass index and risk of amyotrophic lateral sclerosis.  Amyotroph Lateral Scler Frontotemporal Degener. 2013;14(3):205-211.PubMedGoogle ScholarCrossref
16.
Mohanty  P, Ghanim  H, Hamouda  W, Aljada  A, Garg  R, Dandona  P.  Both lipid and protein intakes stimulate increased generation of reactive oxygen species by polymorphonuclear leukocytes and mononuclear cells.  Am J Clin Nutr. 2002;75(4):767-772.PubMedGoogle Scholar
17.
Bloomer  RJ, Fisher-Wellman  KH.  Systemic oxidative stress is increased to a greater degree in young, obese women following consumption of a high fat meal.  Oxid Med Cell Longev. 2009;2(1):19-25.PubMedGoogle ScholarCrossref
18.
Bloomer  RJ, Kabir  MM, Marshall  KE, Canale  RE, Farney  TM.  Postprandial oxidative stress in response to dextrose and lipid meals of differing size.  Lipids Health Dis. 2010;9:79.PubMedGoogle ScholarCrossref
19.
McCarthy  CG, Farney  TM, Canale  RE, Dessoulavy  ME, Bloomer  RJ.  High-fat feeding, but not strenuous exercise, increases blood oxidative stress in trained men.  Appl Physiol Nutr Metab. 2013;38(1):33-41.PubMedGoogle ScholarCrossref
20.
Sies  H, Stahl  W, Sevanian  A.  Nutritional, dietary and postprandial oxidative stress.  J Nutr. 2005;135(5):969-972.PubMedGoogle Scholar
21.
Cedarbaum  JM, Stambler  N, Malta  E,  et al; BDNF ALS Study Group (Phase III).  The ALSFRS-R: a revised ALS functional rating scale that incorporates assessments of respiratory function.  J Neurol Sci. 1999;169(1-2):13-21.PubMedGoogle ScholarCrossref
22.
Brooks  BR, Miller  RG, Swash  M, Munsat  TL; World Federation of Neurology Research Group on Motor Neuron Diseases.  El Escorial revisited: revised criteria for the diagnosis of amyotrophic lateral sclerosis.  Amyotroph Lateral Scler Other Motor Neuron Disord. 2000;1(5):293-299.PubMedGoogle ScholarCrossref
23.
de Carvalho  M, Dengler  R, Eisen  A,  et al.  The Awaji criteria for diagnosis of ALS.  Muscle Nerve. 2011;44(3):456-457.PubMedGoogle ScholarCrossref
24.
Mitsumoto  H, Factor-Litvak  P, Andrews  H,  et al; ALS COSMOS Study Group.  ALS Multicenter Cohort Study of Oxidative Stress (ALS COSMOS): study methodology, recruitment, and baseline demographic and disease characteristics.  Amyotroph Lateral Scler Frontotemporal Degener. 2014;15(3-4):192-203.PubMedGoogle ScholarCrossref
25.
Mitsumoto  H, Brooks  BR, Silani  V.  Clinical trials in amyotrophic lateral sclerosis: why so many negative trials and how can trials be improved?  Lancet Neurol. 2014;13(11):1127-1138.PubMedGoogle ScholarCrossref
26.
Kaufmann  P, Levy  G, Thompson  JL,  et al.  The ALSFRSr predicts survival time in an ALS clinic population.  Neurology. 2005;64(1):38-43.PubMedGoogle ScholarCrossref
27.
Gordon  PH, Miller  RG, Moore  DH.  ALSFRS-R.  Amyotroph Lateral Scler Other Motor Neuron Disord. 2004;5(suppl 1):90-93.PubMedGoogle ScholarCrossref
28.
Elamin  M, Bede  P, Montuschi  A, Pender  N, Chio  A, Hardiman  O.  Predicting prognosis in amyotrophic lateral sclerosis: a simple algorithm.  J Neurol. 2015;262(6):1447-1454.PubMedGoogle ScholarCrossref
29.
Block  G, Hartman  AM, Naughton  D.  A reduced dietary questionnaire: development and validation.  Epidemiology. 1990;1(1):58-64.PubMedGoogle ScholarCrossref
30.
Cummings  SR, Block  G, McHenry  K, Baron  RB.  Evaluation of two food frequency methods of measuring dietary calcium intake.  Am J Epidemiol. 1987;126(5):796-802.PubMedGoogle Scholar
31.
Nieves  JW, Golden  AL, Siris  E, Kelsey  JL, Lindsay  R.  Teenage and current calcium intake are related to bone mineral density of the hip and forearm in women aged 30-39 years.  Am J Epidemiol. 1995;141(4):342-351.PubMedGoogle ScholarCrossref
32.
Serdula  M, Coates  R, Byers  T,  et al.  Evaluation of a brief telephone questionnaire to estimate fruit and vegetable consumption in diverse study populations.  Epidemiology. 1993;4(5):455-463.PubMedGoogle ScholarCrossref
33.
Willett  W.  Nutritional Epidemiology. New York, NY: Oxford University Press; 1989:416.
34.
NutritionQuest. http://www.nutritionquest.com. Accessed September 16, 2016.
35.
Yorita Christensen  KL, Carrico  CK, Sanyal  AJ, Gennings  C.  Multiple classes of environmental chemicals are associated with liver disease: NHANES 2003-2004.  Int J Hyg Environ Health. 2013;216(6):703-709.PubMedGoogle ScholarCrossref
36.
Carrico  C, Gennings  C, Wheeler  DC, Factor-Litvak  P.  Characterization of weighted quantile sum regression for highly correlated data in a risk analysis setting.  J Agric Biol Environ Stat. 2015;20(1):100-120. doi:10.1007/s13253-014-0180-3Google ScholarCrossref
37.
Mahabir  S, Baer  DJ, Giffen  C,  et al.  Calorie intake misreporting by diet record and food frequency questionnaire compared to doubly labeled water among postmenopausal women.  Eur J Clin Nutr. 2006;60(4):561-565.PubMedGoogle ScholarCrossref
38.
Dorst  J, Kühnlein  P, Hendrich  C, Kassubek  J, Sperfeld  AD, Ludolph  AC.  Patients with elevated triglyceride and cholesterol serum levels have a prolonged survival in amyotrophic lateral sclerosis.  J Neurol. 2011;258(4):613-617.PubMedGoogle ScholarCrossref
39.
Zhang  W, Li  P, Hu  X, Zhang  F, Chen  J, Gao  Y.  Omega-3 polyunsaturated fatty acids in the brain: metabolism and neuroprotection.  Front Biosci (Landmark Ed). 2011;16:2653-2670.PubMedGoogle ScholarCrossref
40.
Paganoni  S, Deng  J, Jaffa  M, Cudkowicz  ME, Wills  A-M.  Body mass index, not dyslipidemia, is an independent predictor of survival in amyotrophic lateral sclerosis.  Muscle Nerve. 2011;44(1):20-24.PubMedGoogle ScholarCrossref
41.
Swash  M.  Diet and risk of amyotrophic lateral sclerosis: is lifestyle important?  JAMA Neurol. 2014;71(9):1085-1086.PubMedGoogle ScholarCrossref
42.
Silva  LB, Mourão  LF, Silva  AA,  et al.  Effect of nutritional supplementation with milk whey proteins in amyotrophic lateral sclerosis patients.  Arq Neuropsiquiatr. 2010;68(2):263-268.PubMedGoogle ScholarCrossref
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