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Figure 1.  Association Among Mean Family Genetic Risk Scores (FGRS) for Major Depression, Bipolar Disorder, and Schizophrenia With Psychiatric Diagnoses
Association Among Mean Family Genetic Risk Scores (FGRS) for Major Depression, Bipolar Disorder, and Schizophrenia With Psychiatric Diagnoses

The mean standardized FGRSs and 95% CIs for bipolar disorder and schizophrenia (A), major depression and schizophrenia (B), and major depression and bipolar disorder (C) are shown in association with major depression, bipolar disorder, other nonaffective psychoses (ONAPs), schizoaffective disorder, and schizophrenia from national Swedish samples. For FGRSs in which 95% CIs are not visible, they are contained in the data point. The mean standardized FGRSs and 95% CIs for schizophrenia and major depression (D) and schizophrenia and bipolar disorder (E) are shown for psychotic and nonpsychotic major depression and psychotic and nonpsychotic bipolar disorder.

Figure 2.  Association of Family Genetic Risk Score (FGRS) for Major Depression, Bipolar Disorder, and Schizophrenia With Age at First Registration and Number of Registrations
Association of Family Genetic Risk Score (FGRS) for Major Depression, Bipolar Disorder, and Schizophrenia With Age at First Registration and Number of Registrations

Mean standardized FGRS and 95% CI were estimated from a linear regression model controlling for year of birth.

aP for linear trend: major depression FGRS, <.001; bipolar disorder FGRS, <.001.

bP for linear trend: bipolar disorder FGRS, .09; schizophrenia FGRS, .01.

cP for linear trend: bipolar disorder FGRS, .93; schizophrenia FGRS, .08.

Figure 3.  Association of Family Genetic Risk Score (FGRS) With Diagnostic Conversions in Major Depression and Other Nonaffective Psychoses
Association of Family Genetic Risk Score (FGRS) With Diagnostic Conversions in Major Depression and Other Nonaffective Psychoses

Results of an inverted survival curve applied to all cases, with no application of hierarchy. A, Conversion from a diagnosis of major depression to bipolar disorder by FGRS for bipolar disorder by quintiles. B, Conversion from a diagnosis of other nonaffective psychosis to schizophrenia by FGRS for schizophrenia by quintiles.

Table 1.  Descriptive Results and Mean FGRSs for Major Depression, Bipolar Disorder, and Schizophrenia
Descriptive Results and Mean FGRSs for Major Depression, Bipolar Disorder, and Schizophrenia
Table 2.  Familial Genetic Risk Scores (FGRSs) and 95% CIs for Associations Between Genetic Risk and Clinical Features
Familial Genetic Risk Scores (FGRSs) and 95% CIs for Associations Between Genetic Risk and Clinical Features
Supplement.

eMethods 1. Description of Registers

eTable 1. Definition of Phenotypes

eFigure 1. Diagnostic Hierarchy

eTable 2. First Decision Table

eTable 3. Second Decision Table

eMethods 2. Sensitivity Analyses for Diagnostic Hierarchy

eTable 4. Sensitivity Analysis for Separating Individuals With BD and ONAP

eTable 5. Sensitivity Analysis for Separating Individuals With SZ and ONAP

eFigure 2. FGRS Results Depicted in Figure 1 With and Without Diagnostic Hierarchies

eFigure 3. Flowchart for the Calculation of the Family Genetic Risk Score (FGRS)

eTable 6. Results from the Logistic Regression Models for the Cohabitation Effects

eMethods 3. Sensitivity Analysis for the Genetic Risk Score

eTable 7. Additional Sensitivity Analyses for the Calculation of the Family Genetic Risk Score

eTable 8. Stability of FGRSs for MD, BD and SZ by Median Splits for Cohort and Geographical Region Within Sweden

eFigure 4. Rates of MD in 50 Equaled Sized Groups of the MD FGRS

eFigure 5. Rates of BD in 50 Equaled Sized Groups of the BD FGRS

eFigure 6. Rates of SZ in 50 Equaled Sized Groups of the SZ FGRS

eFigure 7. Similarity of FGRSs for MD, BD, and SZ Across Sexes

eFigure 8. Stability of FGRSs for MD, BD and SZ by Median Splits for Cohort and Geographical Region Within Sweden

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    Original Investigation
    April 21, 2021

    Family Genetic Risk Scores and the Genetic Architecture of Major Affective and Psychotic Disorders in a Swedish National Sample

    Author Affiliations
    • 1Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond
    • 2Department of Psychiatry, Virginia Commonwealth University, Richmond
    • 3Center for Primary Health Care Research, Lund University, Malmö, Sweden
    • 4Department of Family Medicine and Community Health, Icahn School of Medicine at Mount Sinai, New York, New York
    • 5Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York
    JAMA Psychiatry. 2021;78(7):735-743. doi:10.1001/jamapsychiatry.2021.0336
    Key Points

    Questions  Do family genetic risk scores (FGRSs) clarify the genetic relationship between major affective and psychotic disorders, and does genetic risk affect clinical features?

    Findings  In this national Swedish cohort study of 4.1 million individuals, FGRSs produced clear separations between major affective and psychotic disorders and were associated with early age at onset and high rates of recurrence. The FGRS for schizophrenia clearly distinguished the psychotic and nonpsychotic forms of major depression and bipolar illness.

    Meaning  These findings provide validation, from a genetic perspective, for these major diagnostic categories and extend prior observations of the association of FGRS with age at onset, recurrence, psychotic subtypes, and diagnostic conversions.

    Abstract

    Importance  Family and genetic approaches have traditionally been used to evaluate our diagnostic concepts. Using a novel method, the family genetic risk score (FGRS), can we validate the genetic architecture of major affective and psychotic disorders in a national Swedish sample?

    Objective  To determine whether FGRSs, calculated for the entire Swedish population, can elucidate the genetic relationship between major affective and psychotic disorders and clarify the association of genetic risk with important clinical features of disease.

    Design, Setting, and Participants  This cohort study included the native Swedish population born from January 1, 1950, through December 31, 1995, and followed up through December 31, 2017. Data were collected from Swedish population-based primary care, specialist, and hospital registers, including age at first registration for a psychiatric diagnosis and number of registrations for major depression, bipolar disorder, and schizophrenia. Data were analyzed from October 15, 2020, to February 2, 2021.

    Exposures  FGRSs for major depression, bipolar disorder, and schizophrenia calculated from morbidity risks for disorders in first- through fifth-degree relatives, controlling for cohabitation.

    Main Outcomes and Measures  Diagnoses of major depression, bipolar disorder, schizophrenia, schizoaffective disorder, and other nonaffective psychoses (ONAPs), age at registration, and number of registrations for major depression, bipolar disorder, and schizophrenia. Diagnostic conversion of major depression to bipolar disorder and ONAPs to schizophrenia was assessed by Cox proportional hazards regression models.

    Results  The cohort included 4 129 002 individuals (51.4% male) with a mean (SD) age at follow-up of 45.5 (13.4) years. Mean FGRSs for major depression, bipolar disorder, and schizophrenia produced distinct patterns for major depression, bipolar disorder, schizophrenia, schizoaffective disorder, and ONAPs with large separations between disorders. In major depression, bipolar disorder, and schizophrenia, high FGRSs were associated with early age at onset and high rates of recurrence: a high mean FGRS for bipolar disorder was associated with early age at onset (younger than 25 years, 0.11; 95% CI, 0.11-0.12) and higher recurrence (8 or more registrations, 0.11; 95% CI, 0.11-0.12) in major depression. The schizophrenia FGRS was separately associated with psychotic and nonpsychotic forms of major depression (0.10; 95% CI, 0.06-0.14 vs 0.03; 95% CI, 0.02-0.03) and bipolar disorder (0.22; 95% CI, 0.16-0.28 vs 0.11; 95% CI, 0.09-0.12). The bipolar disorder and schizophrenia FGRSs were associated with conversion from major depression to bipolar disorder (eg, hazard ratio, 1.70 [95% CI, 1.63-1.78] for high vs low bipolar FGRS) and ONAP to schizophrenia (eg, hazard ratio, 1.38 [95% CI, 1.27-1.51] for high vs low schizophrenia FGRS).

    Conclusions and Relevance  In this Swedish cohort study, the FGRSs for major depression, bipolar disorder, and schizophrenia for the Swedish population clearly separated major affective and psychotic disorders from each other in a larger and more representative patient sample than previously possible. These findings provide possible validation, from a genetic perspective, for these major diagnostic categories. These results replicated and extended prior observations on more limited samples of the association of FGRS with age at onset, recurrence, psychotic subtypes, and diagnostic conversions.

    Introduction

    The interrelationship and validity of major psychiatric diagnoses have been evaluated by several different genetic strategies.1-3 Family studies have established the separation of bipolar disorder and major depression with clear differences in rates of these affective disorders in the relatives of probands with bipolar disorder and major depression.4,5 Adoption studies have provided empirical evidence for the schizophrenia spectrum personality disorders.6,7 Multivariate twin studies have supported the division of common psychiatric disorders into internalizing and externalizing subgroups.8 Aggregated common variants from genome-wide association studies have examined the genetic interrelationships between pairs9 and groups10 of psychiatric disorders. Such strategies have also been used for more focused questions, such as the association between genetic risk and early age at onset, recurrence, and diagnostic changes over time.11-13

    We add to this long empirical tradition by using a novel method of assessing genetic risk: the family genetic risk score (FGRS). We calculated the FGRSs for major depression, bipolar disorder, and schizophrenia from the rates of illness in first- through fifth-degree relatives in the Swedish population and examined these risk scores in population-based cohorts of individuals with 5 major affective and psychotic disorders: major depression, bipolar disorder, schizophrenia, schizoaffective disorder, and other nonaffective psychoses (ONAPs). We herein address the following 4 questions. First, how well do the patterns of FGRSs for major depression, bipolar disorder, and schizophrenia discriminate these 5 disorders? Second, are the FGRSs for major depression, bipolar disorder, and schizophrenia associated with age at first registration for the psychiatric diagnosis and the number of registrations for each disorder? Third, can FGRS patterns clearly distinguish psychotic and nonpsychotic forms of major depression and bipolar disorder? Fourth, among individuals with a first diagnosis of major depression, is the FGRS for bipolar disorder associated with conversion to bipolar disorder, and among those with a diagnosis of ONAP, is the FGRS for schizophrenia associated with the future development of schizophrenia?

    Although the FGRS, like the polygenic risk score (PRS), attempts to measure aggregate genetic risk, these scores are fundamentally different measures. The FGRS is based on rates of phenotypes—herein psychiatric disorders—in relatives with corrections for age, sex, year of birth, area of residence, and association with cohabitation. The PRS is based on a sum of DNA sequence variants that differ in genome-wide association studies of cases and controls. Although the PRS, which is based on thousands of variants, has a classical Gaussian distribution, the FGRS, as seen in eFigures 4 to 6 in the Supplement, has skewed distributions that are more pronounced for rarer disorders.

    Methods

    For this cohort study, we collected information on individuals from Swedish population-based registers with national coverage linking each person’s unique personal identification number, which was replaced with a serial number by Statistics Sweden to preserve confidentiality (eMethods 1 in the Supplement). We secured ethical approval for this study from the regional ethical review board in Lund, Sweden, which did not require participant consent for the use of these data. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.

    Our database consisted of all individuals born in Sweden to Swedish-born parents from January 1, 1950, through December 31, 1995. Follow-up ended on December 31, 2017, and data were analyzed from October 15, 2020, to February 2, 2021. In the database, we included registrations for major depression, bipolar disorder, schizophrenia, schizoaffective disorder, and ONAPs using codes from International Classification of Diseases, Eighth Revision, International Classification of Diseases, Ninth Revision, and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) from primary care, specialist, and hospital registries (eTable 1 in the Supplement). In the analyses, we used a hierarchy based on the number and timing of diagnoses in the registers so that an individual could only be considered as registered with a diagnosis of major depression, bipolar disorder, schizophrenia, schizoaffective disorder, or ONAP in our analyses (eFigure 1 and eTables 2 and 3 in the Supplement). For individuals with major depression and bipolar disorder, we further included psychotic and nonpsychotic forms (eTable 1 in the Supplement). We also included an individual FGRS for major depression, bipolar disorder, and schizophrenia based on a mean of 32.2 first-, second-, third-, fourth-, and fifth-degree relatives of the proband. Briefly (eFigure 3 in the Supplement), we first calculated the morbid risk for the phenotype based on age at first registration. Thereafter, we transformed the binary trait into an underlying liability distribution and calculated the mean z score for relatives with and without the trait. For first-degree relatives, we also multiplied the z score with a factor that controlled for the association with cohabitation (see eTable 6 in the Supplement). Within each type of relative, we then had 2 components: the sum of the z scores and the total weighted number of relatives. These 2 components were further weighted by their genetic resemblance to the proband. For each proband, we summed the 2 components across all groups of relatives and used the quotient, which was then multiplied by a shrinkage factor to take into account the number of relatives of the proband. To make the FGRS comparable across traits, we standardized the FGRS, based on year of birth and county of residence, into a z score with a mean of 0 and SD of 1. We explore the robustness of our FGRS to changes in methodology in eTable 7 and eFigures 7 and 8 in the Supplement. Sensitivity analyses for diagnostic hierarchy and FGRS are found in eMethods 2 and 3 in the Supplement.

    For question 1 (patterns of FGRS for major depression, bipolar disorder, and schizophrenia), we calculated the mean FGRS with corresponding 95% CIs for individuals with major depression, bipolar disorder, schizophrenia, schizoaffective disorder, and ONAPs. For the first part of question 2 (FGRS and age at onset), we categorized age at first registration as a proxy for age at onset (for major depression, bipolar disorder, and schizophrenia) into 5 equal-sized groups. We calculated the least-squares means for the 5 different groups. For individuals registered with major depression and bipolar disorder, we investigated the effects of the FGRS for each disorder separately. For individuals with schizophrenia, we investigated the bipolar disorder and schizophrenia FGRSs separately.

    For the second part of question 2 (FGRS and number of registrations), we categorized the number of registrations as a proxy for recurrence (for major depression, bipolar disorder, and schizophrenia) into quintiles and calculated the least-squares means for the 5 different groups. For individuals registered with major depression and bipolar disorder, we investigated the FGRS for each disorder separately. For individuals with schizophrenia, we investigated the bipolar disorder and schizophrenia FGRSs separately.

    For question 3 (differentiation between psychotic and nonpsychotic forms of major depression and bipolar disorder), we calculated the mean FGRS with corresponding 95% CIs for individuals with psychotic and nonpsychotic forms of major depression and bipolar disorder, the diagnoses of which are only available in ICD-10. For question 4 (conversion to bipolar disorder and schizophrenia among individuals with major depression and ONAPs, respectively), we first categorized the FGRS for bipolar disorder and schizophrenia into quintiles and then calculated the time to bipolar disorder or schizophrenia from the first registration of major depression or ONAPs. We used a Cox proportional hazards regression model to investigate the time to bipolar disorder or schizophrenia while controlling for age at registration for major depression or ONAPs and did not apply the diagnostic hierarchy. We also present 1 minus the survival curve at the mean age at registration. All statistical analyses were performed using SAS, version 9.4.14 We used a 2-sided t test to test for equality between the mean values of the different groups, with P < .05 indicating statistical significance.

    Results
    Sample Description

    Our sample included 4 129 002 individuals (51.4% male and 48.6% female), with a mean age (SD) age of 45.5 (13.4) years at the close of ascertainment on December 31, 2017. Table 1 provides descriptive statistics for our diagnostic groups. Population prevalence ranged from 0.12% for schizoaffective disorder to 12.0% for major depression. We noted a female preponderance for major depression (63.3%), bipolar disorder (61.9%), and schizoaffective disorder (56.3%); a male preponderance for schizophrenia (66.3%) and ONAPs (55.7%); and higher proportions of patients with bipolar disorder (9.2%) than major depression (1.0%) with a diagnosis of a psychotic subtype.

    FGRS Patterns and Discrimination Between Different Disorders

    Figure 1 illustrates the associations found in this study among the mean major depression, bipolar disorder, and schizophrenia FGRSs expressed as a z score for our 5 diagnostic categories, the results of which are also depicted in Table 1. Figure 1A depicts the placement of the disorders by their mean bipolar disorder and schizophrenia FGRSs on the x- and y-axes. The disorders are widely separated from each other in this Figure. Major depression is close to the lower left corner with very modest FGRSs for bipolar disorder and schizophrenia. Schizophrenia appears in the upper left corner with a high mean schizophrenia FGRS and a much lower bipolar disorder FGRS. Bipolar disorder is in the lower right corner with a high bipolar disorder FGRS but a low schizophrenia FGRS. Schizoaffective disorder appears midway between schizophrenia and bipolar disorder, with similar elevations of schizophrenia and bipolar disorder FGRSs. Other nonaffective psychoses had a much lower schizophrenia FGRS than schizophrenia and a much lower bipolar disorder FGRS than bipolar disorder.

    Figure 1B shows the disorders by their major depression and schizophrenia FGRSs on the x- and y-axes. Major depression and bipolar disorder are relatively close to one another in the right lower quadrant of the graph, with a high major depression FGRS and low schizophrenia FGRS. Schizophrenia is in the upper left quadrant with a low major depression FGRS. Other nonaffective psychoses and schizoaffective disorder had similar levels of major depression FGRS, with schizoaffective disorder having a higher schizophrenia FGRS.

    Figure 1C shows the disorders by their major depression and bipolar disorder FGRSs on the x- and y-axes. Schizophrenia is close to the lower left corner, with a low major depression FGRS and somewhat higher bipolar disorder FGRS. Bipolar disorder appears in the upper right corner, with high major depression and bipolar disorder FGRSs; major depression is in the lower right quadrant, with a high major depression FGRS but a low bipolar disorder FGRS. In this study, schizoaffective disorder and ONAPs were clearly differentiated from one another, with schizoaffective disorder having a higher bipolar disorder than major depression FGRS and ONAPs having similar risk scores.

    Association of FGRS With Age at Onset and Recurrence

    As seen in Figure 2A, a first registration for major depression before 25 years of age was associated with increased mean FGRSs for major depression and bipolar disorder, but little difference was seen in FRGSs between later ages at first registration. For bipolar disorder, first registration before 31 years of age was associated with a higher mean bipolar disorder FGRS but a lower mean major depression FGRS. Early age at registration for schizophrenia was associated with a higher mean schizophrenia FGRS, but the association with bipolar disorder FGRS was not significant.

    Figure 2B presents for the association between levels of recurrence (ie, number of independent registrations) and FGRSs for major depression, bipolar disorder, and schizophrenia. The FGRS was associated with the number of diagnoses in the registries for major depression and especially bipolar disorder, with the association being present but weaker for schizophrenia. The mean FGRS for bipolar disorder had a positive association with recurrence risk in major depression but not schizophrenia. The major depression FGRS had no systematic association with the number of bipolar disorder episodes. The FGRSs and 95% CIs for the results depicted in Figure 2 are provided in Table 2.

    FGRS and Differentiation of Psychotic and Nonpsychotic Forms of Major Depression and Bipolar Disorder

    Figure 1D depicts the findings for placement of the psychotic and nonpsychotic forms of major depression and bipolar disorder as a function of their major depression and schizophrenia FGRSs on the x- and y-axes. Nonpsychotic and psychotic major depression had a similar major depression FGRS, but the psychotic form had higher schizophrenia FGRS. The findings for nonpsychotic and psychotic bipolar disorder were different in that psychotic bipolar disorder had a higher schizophrenia FGRS and a lower major depression FGRS.

    Figure 1E, which presents the placement of the psychotic and nonpsychotic forms of major depression and bipolar disorder as a function of their bipolar disorder FGRS on the x-axis and schizophrenia FGRS on the y-axis, depicts different findings. For both bipolar disorder and major depression, the psychotic form differed from the nonpsychotic form in that it had both higher mean schizophrenia and higher mean bipolar disorder FGRSs. These differences were greater in cases of bipolar disorder than in cases of major depression. The FGRSs and 95% CIs for the results depicted in Figure 1D and E are provided in Table 2.

    Association of FGRS Scores With Diagnostic Conversions in Major Depression and ONAPs

    Finally, we assessed the association between FGRSs for bipolar disorder and schizophrenia with diagnostic conversions from major depression to bipolar disorder and ONAPs to schizophrenia. Figure 3A depicts an inverse survival curve for the proportion of individuals with an initial diagnosis of major depression who receive a subsequent diagnosis of bipolar disorder as a function of the quintile of their bipolar disorder FGRS. Small differences in risk are displayed across the lower 4 quintiles, whereas those individuals with a bipolar disorder FGRS in the highest quintile had a substantially increased risk of having their diagnosis converted to bipolar disorder. In Figure 3B, similar results are presented. The conversion to schizophrenia in those with an initial ONAP diagnosis was substantially higher in those in the highest quintile of schizophrenia FGRS.

    Discussion

    We applied a new measure of aggregate genetic risk to a national sample of treated patients with major affective and psychotic disorders in Sweden. We thereby addressed 4 questions about the degree to which FGRSs for major depression, bipolar disorder, and schizophrenia were associated and may distinguish between major affective and psychotic disorders and their key clinical features.

    First, FGRSs for major depression, bipolar disorder, and schizophrenia robustly separated major depression, bipolar disorder, schizophrenia, schizoaffective disorder, and ONAPs from each other. We found a clearer separation of the genetic risk for schizophrenia and bipolar disorder than that seen in a large-scale twin and nontwin sibling analysis in Sweden15 or in molecular genetic studies.10,16 To address the stability of this finding, we examined the association between schizophrenia and bipolar disorder separately in male and female individuals and obtained a similar finding in both sexes (eFigure 7 in the Supplement). Our results for schizoaffective disorder—with an FGRS pattern midway between those of bipolar disorder and schizophrenia—are consistent with findings from the Iowa 50017 and Roscommon family18 studies and molecular genetic investigations.19

    Second, for major depression, bipolar disorder, and schizophrenia, high FGRSs were associated with early age at onset. As shown in 1 prior study,20 high bipolar disorder PRS was significantly associated with early age of onset and recurrence rates for major depression. Our results are consistent with several family and twin studies showing an association between familial and/or genetic risk for major depression and early age at onset,21-23 although this was not replicated by a PRS analysis.24 A prior study of major depression in Swedish twins found, as we did, that the association of age at onset with genetic risk for major depression disappears in later-onset cases.23 Family study data also show an inverse association of familial risk and age at onset in bipolar disorder,21,25 although this finding was not replicated using molecular genetic methods.26 The association between age at onset and genetic risk has been less clear in schizophrenia, with 1 molecular genetic study showing a clear association13 but family studies showing more negative results.27-29 Consistent with our results, a study using measures of polygenic heritability30 found stronger genetic effects in cases of schizophrenia with high vs low levels of recurrence.

    We found particularly robust associations between FGRS and recurrence in major depression, bipolar disorder, and schizophrenia. These results are consistent with prior evidence that recurrence in major depression is an index of familial risk31-33 and that elevated molecular genetic risk for schizophrenia is associated with recurrence.30 Bipolar disorder FGRS also is associated with recurrence in major depression, although we have been unable to find prior studies confirming this association.33

    Third, consistent with family studies reporting higher rates of schizophrenia in relatives of patients with psychotic vs nonpsychotic affective disorder17,34,35 and molecular genetic studies reporting similar patterns with PRS,19,36,37 we found clear separations in the pattern of FGRS in psychotic vs nonpsychotic major depression and bipolar disorder. We also observed findings that to our knowledge have not been observed previously. Although psychotic and nonpsychotic forms of major depression and bipolar disorder had a similar major depression FGRS, the psychotic forms of both disorders were associated with an elevated bipolar disorder FGRS.

    Fourth, congruent with evidence using both family and molecular designs,11,38-42 individuals with major depression at high genetic risk for bipolar disorder had a considerably elevated rate of conversion to bipolar disorder. We could usefully compare our specific results with those obtained recently using the PRS from a Danish national sample.11 Using similar controls, the authors reported a hazard ratio for a standardized bipolar disorder PRS of 1.11 (95% CI, 1.03-1.21) for the association of major depression conversion with bipolar disorder,11 statistically consistent with our results. In our sample, a high schizophrenia FGRS was associated with diagnostic conversion from ONAPs to schizophrenia. The finding most similar to this of which we are aware emerged from the Suffolk County Mental Health Project, where a schizophrenia PRS was associated with diagnostic shifts, over time, from affective psychotic to nonaffective psychotic disorders.12

    Although most of our results were consistent with prior expectations, one was not. We expected the genetic profile of ONAPs to closely resemble that of schizophrenia. This was not the case (Figure 1A and B). Compared with schizophrenia (which we defined narrowly, excluding latent, simple, acute, and schizoaffective forms), ONAPs had a much lower schizophrenia FGRS. These findings call into question the validity, from a genetic perspective, of constructs such as nonaffective psychoses or broadly defined schizophrenia that would typically include individuals with a schizophrenia diagnosis and a substantial proportion of those defined herein as having ONAPs.

    Limitations

    These findings should be viewed in the context of 4 potential methodological limitations. First, we cannot rule out that clinicians knew the family history of their patients and that knowledge influenced their diagnoses. Second, the validity of FGRS depends on the quality of diagnoses in the Swedish national registries, which for hospital diagnoses of schizophrenia and bipolar disorder have been well supported.43-45 The validity of major depression diagnoses is supported by its prevalence, sex ratio, sibling and twin correlations, and associations with known psychosocial risk factors.46,47 Third, we applied algorithms to establish diagnostic hierarchies for our cases. We outline these in eFigure 1 and in eTables 2 and 3 in the Supplement, showing that changes in the hierarchies (eTables 4 and 5 in the Supplement) or their complete elimination (eFigure 2 in the Supplement) produced only modest alterations in results. Fourth, given the novelty of our FGRS method, we explored its stability across sex, time, and space in eFigures 7 and 8 in the Supplement. We examined 21 comparisons of FRGS in major depression, bipolar disorder, and schizophrenia in the 2 sexes, in the older and younger halves of our cohort (1950-1972 vs 1972-1995), and in southern and northern Sweden. Three of these comparisons were significant at a chance corrected P < .002, and for all of these comparisons, the observed differences were quantitatively modest.

    Conclusions

    By assessing an individual’s genetic risk based on rates of disorder in their immediate and extended relatives and controlling for the association with cohabitation, the FGRSs for major depression, bipolar disorder, and schizophrenia, available for the entire Swedish population, performed well in separating major affective and psychotic disorders on larger and more representative patient samples than has hitherto been possible. In so doing, these FGRSs provide possible validation for these major, albeit imperfect, diagnostic categories. The application of FGRS was also able to replicate and extend prior observations based on smaller samples of (1) higher genetic loading for early-onset and highly recurrent cases of major depression, bipolar disorder, and schizophrenia; (2) differences in genetic risk profiles for psychotic and nonpsychotic major depression and bipolar disorder; and (3) the association of bipolar disorder and schizophrenia FGRSs with diagnostic conversions from major depression to bipolar disorder and from ONAPs to schizophrenia, respectively. Our findings suggest that FGRSs, which are available in countries with high-quality population and medical registries, could have many additional potentially valuable research applications.

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    Article Information

    Accepted for Publication: February 11, 2021.

    Published Online: April 21, 2021. doi:10.1001/jamapsychiatry.2021.0336

    Corresponding Author: Kenneth S. Kendler, MD, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, PO Box 980126, Richmond, VA 23298 (kenneth.kendler@vcuhealth.org).

    Author Contributions: Dr Sundquist had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

    Concept and design: Kendler, Ohlsson, K. Sundquist.

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

    Drafting of the manuscript: Kendler.

    Critical revision of the manuscript for important intellectual content: All authors.

    Statistical analysis: Kendler, Ohlsson.

    Obtained funding: Kendler, J. Sundquist, K. Sundquist.

    Administrative, technical, or material support: J. Sundquist, K. Sundquist.

    Supervision: Kendler, K. Sundquist.

    Conflict of Interest Disclosures: None reported.

    Funding/Support: This study was supported by grants R01AA023534 and R01DA030005 from the National Institutes of Health and grant 2016-01176 from the Swedish Research Council, as well as Avtal om Läkarutbildning och Forskning funding from Region Skåne.

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

    Additional Information: This study was performed at Lund University and Virginia Commonwealth University.

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