Genetic structure correlates with ethnolinguistic diversity in eastern and southern Africa.

African populations are the most diverse in the world yet are sorely underrepresented in medical genetics research. Here, we examine the structure of African populations using genetic and comprehensive multi-generational ethnolinguistic data from the Neuropsychiatric Genetics of African Populations-Psychosis study (NeuroGAP-Psychosis) consisting of 900 individuals from Ethiopia, Kenya, South Africa, and Uganda. We find that self-reported language classifications meaningfully tag underlying genetic variation that would be missed with consideration of geography alone, highlighting the importance of culture in shaping genetic diversity. Leveraging our uniquely rich multi-generational ethnolinguistic metadata, we track language transmission through the pedigree, observing the disappearance of several languages in our cohort as well as notable shifts in frequency over three generations. We find suggestive evidence for the rate of language transmission in matrilineal groups having been higher than that for patrilineal ones. We highlight both the diversity of variation within Africa as well as how within-Africa variation can be informative for broader variant interpretation; many variants that are rare elsewhere are common in parts of Africa. The work presented here improves the understanding of the spectrum of genetic variation in African populations and highlights the enormous and complex genetic and ethnolinguistic diversity across Africa.

Low-coverage sequencing cost-effectively detects known and novel variation in underrepresented populations.

Genetic studies in underrepresented populations identify disproportionate numbers of novel associations. However, most genetic studies use genotyping arrays and sequenced reference panels that best capture variation most common in European ancestry populations. To compare data generation strategies best suited for underrepresented populations, we sequenced the whole genomes of 91 individuals to high coverage as part of the Neuropsychiatric Genetics of African Population-Psychosis (NeuroGAP-Psychosis) study with participants from Ethiopia, Kenya, South Africa, and Uganda. We used a downsampling approach to evaluate the quality of two cost-effective data generation strategies, GWAS arrays versus low-coverage sequencing, by calculating the concordance of imputed variants from these technologies with those from deep whole-genome sequencing data. We show that low-coverage sequencing at a depth of ≥4× captures variants of all frequencies more accurately than all commonly used GWAS arrays investigated and at a comparable cost. Lower depths of sequencing (0.5-1×) performed comparably to commonly used low-density GWAS arrays. Low-coverage sequencing is also sensitive to novel variation; 4× sequencing detects 45% of singletons and 95% of common variants identified in high-coverage African whole genomes. Low-coverage sequencing approaches surmount the problems induced by the ascertainment of common genotyping arrays, effectively identify novel variation particularly in underrepresented populations, and present opportunities to enhance variant discovery at a cost similar to traditional approaches.

Relationships between trauma types and psychotic symptoms: A network analysis of patients with psychotic disorders in a large, multi-country study in East Africa.

BACKGROUND: The link between trauma exposure and psychotic disorders is well-established. Further, specific types of trauma may be associated with specific psychotic symptoms. Network analysis is an approach that can advance our understanding of the associations across trauma types and psychotic symptoms. METHODS: We conducted a network analysis with data from 16,628 adult participants (mean age [standard deviation] = 36.3 years [11.5]; 55.8% males) with psychotic disorders in East Africa recruited between 2018 and 2023. We used the Life Events Checklist and the Mini International Neuropsychiatric Interview to determine whether specific trauma types experienced over the life course and specific psychotic symptoms were connected. We used an Ising model to estimate the network connections and bridge centrality statistics to identify nodes that may influence trauma types and psychotic symptoms. RESULTS: The trauma type "exposure to a war zone" had the highest bridge strength, betweenness, and closeness. The psychotic symptom "odd or unusual beliefs" had the second highest bridge strength. Exposure to a war zone was directly connected to visual hallucinations, odd or unusual beliefs, passivity phenomena, and disorganized speech. Odd or unusual beliefs were directly connected to transportation accidents, physical assault, war, and witnessing sudden accidental death. CONCLUSION: Specific trauma types and psychotic symptoms may interact bidirectionally. Screening for psychotic symptoms in patients with war-related trauma and evaluating lifetime trauma in patients with odd or unusual beliefs in clinical care may be considered points of intervention to limit stimulating additional psychotic symptoms and trauma exposure. This work reaffirms the importance of trauma-informed care for patients with psychotic disorders.

Evaluation of the psychometric properties of the UBACC questionnaire in a multi-country psychiatric study in Africa.

BACKGROUND: The University of California, San Diego Brief Assessment of Capacity to Consent (UBACC) is a tool to assess the capacity of participants to consent in psychiatric research. However, little is known about the psychometric properties in low and middle-income countries. This study aimed to examine the psychometric properties of the UBACC. METHODS: We examined the reliability, latent factor structure, and item response of the first attempt of the UBACC items in a sample of 32,208 adults (16,467 individuals with psychosis and 15,741 controls) in Ethiopia, Kenya, South Africa, and Uganda; exploring these properties in the full sample and stratified by country, diagnostic status, sex, and ethnolinguistic language groups. RESULTS: Exploratory factor analysis (EFA) suggested a two-factor model for the overall sample. However, a three-factor model was more appropriate when examining the latent structure across country, language, and sex. Confirmatory factor analyses (CFA) revealed an adequately fitting three-factor model for the full sample and across country, sex, and language. A two-factor model, however, was more appropriate for English and Amharic languages. Across all groups, the internal consistency of the UBACC was low, indicating below-threshold reliability (Cronbach's α (95 % CI = 0.58 (0.57-0.59). Using a multidimensional item-response theory framework for the full sample revealed that UBACC item 8, measuring understanding of the benefits of study participation, was the most discriminating item. Many of the other items had below-threshold discriminating characteristics. CONCLUSION: EFA and CFA converged towards a two and three-dimensional structure for the UBACC, in line with the developers of the original scale. The differences in properties between populations and language groups, low internal consistency, and below-threshold item functioning suggest that investigations into the cultural and linguistic nuances are still warranted. Understanding the utility of consent tools, such as the UBACC, in underrepresented populations will be a part of the larger process which ensures that research participants are adequately protected.

Psychometric properties of the mini international neuropsychiatric interview (MINI) psychosis module: a Sub-Saharan Africa cross country comparison.

BACKGROUND: The Mini International Neuropsychiatric Inventory 7.0.2 (MINI-7) is a widely used tool and known to have sound psychometric properties; but very little is known about its use in low and middle-income countries (LMICs). This study aimed to examine the psychometric properties of the MINI-7 psychosis items in a sample of 8609 participants across four countries in Sub-Saharan Africa. METHODS: We examined the latent factor structure and the item difficulty of the MINI-7 psychosis items in the full sample and across four countries. RESULTS: Multiple group confirmatory factor analyses (CFAs) revealed an adequate fitting unidimensional model for the full sample; however, single group CFAs at the country level revealed that the underlying latent structure of psychosis was not invariant. Specifically, although the unidimensional structure was an adequate model fit for Ethiopia, Kenya, and South Africa, it was a poor fit for Uganda. Instead, a 2-factor latent structure of the MINI-7 psychosis items provided the optimal fit for Uganda. Examination of item difficulties revealed that MINI-7 item K7, measuring visual hallucinations, had the lowest difficulty across the four countries. In contrast, the items with the highest difficulty were different across the four countries, suggesting that MINI-7 items that are the most predictive of being high on the latent factor of psychosis are different for each country. CONCLUSIONS: The present study is the first to provide evidence that the factor structure and item functioning of the MINI-7 psychosis vary across different settings and populations in Africa.

Association between psychosis and substance use in Kenya. Findings from the NeuroGAP-Psychosis study.

Background: Substance use is prevalent among people with mental health issues, and patients with psychosis are more likely to use and misuse substances than the general population. Despite extensive research on substance abuse among the general public in Kenya, there is a scarcity of data comparing substance use among people with and without psychosis. This study investigates the association between psychosis and various substances in Kenya. Methods: This study utilized data from the Neuro-GAP Psychosis Case-Control Study between April 2018 and December 2022. The KEMRI-Wellcome Trust Research Programme recruited participants from various sites in Kenya, including Kilifi County, Malindi Sub-County, Port Reitz and Coast General Provincial Hospitals, and Moi Teaching and Referral Hospital, as well as affiliated sites in Webuye, Kapenguria, Kitale, Kapsabet, and Iten Kakamega. The collected data included sociodemographic information, substance use, and clinical diagnosis. We used the summary measures of frequency (percentages) and median (interquartile range) to describe the categorical and continuous data, respectively. We examined the association between categorical variables related to psychosis using the chi-square test. Logistic regression models were used to assess the factors associated with the odds of substance use, considering all relevant sociodemographic variables. Results: We assessed a total of 4,415 cases and 3,940 controls. Except for alcohol consumption (p-value=0.41), all forms of substance use showed statistically significant differences between the case and control groups. Cases had 16% higher odds of using any substance than controls (aOR: 1.16, 95%CI: 1.05-1.28, p=0.005). Moreover, males were 3.95 times more likely to use any substance than females (aOR:3.95; 95%CI: 3.43-4.56). All the categories of living arrangements were protective against substance use. Conclusion: The findings of this study suggest that psychotic illnesses are associated with an increased likelihood of using various substances. These findings are consistent with those of previous studies; however, it is crucial to investigate further the potential for reverse causality between psychosis and substance abuse using genetically informed methods.

Cross-cultural equivalence of the Kessler Psychological Distress Scale (K10) across four African countries in a multi-national study of adults.

The Kessler Psychological Distress Scale (K10) has been widely used to screen psychological distress across many countries. However, its performance has not been extensively studied in Africa. The present study sought to evaluate and compare measurement properties of the K10 across four African countries: Ethiopia, Kenya, Uganda, and South Africa. Our hypothesis is that the measure will show equivalence across all. Data are drawn from a neuropsychiatric genetic study among adult participants (N = 9179) from general medical settings in Ethiopia (n = 1928), Kenya (n = 2556), Uganda (n = 2104), and South Africa (n = 2591). A unidimensional model with correlated errors was tested for equivalence across study countries using confirmatory factor analyses and the alignment optimization method. Results displayed 30 % noninvariance (i.e., variation) for both intercepts and factor loadings across all countries. Monte Carlo simulations showed a correlation of 0.998, a good replication of population values, indicating minimal noninvariance, or variation. Items "so nervous," "lack of energy/effortful tasks," and "tired" were consistently equivalent for intercepts and factor loadings, respectively. However, items "depressed" and "so depressed" consistently differed across study countries (R2 = 0) for intercepts and factor loadings for both items. The K10 scale likely functions equivalently across the four countries for most items, except "depressed" and "so depressed." Differences in K10 items were more common in Kenya and Ethiopia, suggesting cultural context may influence the interpretation of some items and the potential need for cultural adaptations in these countries.

Psychological Distress Among Ethnically Diverse Participants From Eastern and Southern Africa.

Importance: Psychological distress is characterized by anxiety and depressive symptoms. Although prior research has investigated the occurrence and factors associated with psychological distress in low- and middle-income countries, including those in Africa, these studies' findings are not very generalizable and have focused on different kinds of population groups. Objective: To investigate the prevalence and characteristics (sociodemographic, psychosocial, and clinical) associated with psychological distress among African participants. Design, setting, and participants: This case-control study analyzed data of participants in the Neuropsychiatric Genetics in African Populations-Psychosis (NeuroGAP-Psychosis) study, which recruited from general outpatient clinics in Eastern (Uganda, Kenya, and Ethiopia) and Southern (South Africa) Africa. Individuals who participated in the control group of NeuroGAP-Psychosis from 2018 to 2023 were analyzed as part of this study. Data were analyzed from May 2023 to January 2024. Main outcomes and measures: The prevalence of psychological distress was determined using the Kessler Psychological Distress Scale (K10), which measures distress on a scale of 10 to 50, with higher scores indicating more distress. Participants from the NeuroGAP-Psychosis study were categorized into cases as mild (score of 20-24), moderate (score of 25-29), and severe (score of 30-50), and participants with scores less than 20 were considered controls. Factors that were associated with psychological distress were examined using binomial logistic regression. Results: From the data on 21 308 participants, the mean (SD) age was 36.5 (11.8) years, and 12 096 participants (56.8%) were male. The majority of the participants were married or cohabiting (10 279 participants [48.2%]), most had attained secondary education as their highest form of learning (9133 participants [42.9%]), and most lived with their families (17 231 participants [80.9%]). The prevalence of mild, moderate, and severe psychological distress was 4.2% (869 participants), 1.5% (308 participants), and 0.8% (170 participants), respectively. There were 19 961 participants (93.7%) who served as controls. Binomial logistic regression analyses indicated that the independent associations of psychological distress were experience of traumatic events, substance use (alcohol, tobacco, or cannabis), the physical comorbidity of arthritis, chronic neck or back pain, and frequent or severe headaches. Conclusions and relevance: In this case-control study among ethnically diverse African participants, psychological distress was associated with traumatic stress, substance use, and physical symptoms. These findings were observed to be consistent with previous research that emphasizes the importance of traumatic events as a factor associated with risk for psychopathology and notes the frequent co-occurrence of conditions such as physical symptoms, depression, and anxiety.

A blended genome and exome sequencing method captures genetic variation in an unbiased, high-quality, and cost-effective manner.

We deployed the Blended Genome Exome (BGE), a DNA library blending approach that generates low pass whole genome (1-4× mean depth) and deep whole exome (30-40× mean depth) data in a single sequencing run. This technology is cost-effective, empowers most genomic discoveries possible with deep whole genome sequencing, and provides an unbiased method to capture the diversity of common SNP variation across the globe. To evaluate this new technology at scale, we applied BGE to sequence >53,000 samples from the Populations Underrepresented in Mental Illness Associations Studies (PUMAS) Project, which included participants across African, African American, and Latin American populations. We evaluated the accuracy of BGE imputed genotypes against raw genotype calls from the Illumina Global Screening Array. All PUMAS cohorts had R 2 concordance ≥95% among SNPs with MAF≥1%, and never fell below ≥90% R 2 for SNPs with MAF<1%. Furthermore, concordance rates among local ancestries within two recently admixed cohorts were consistent among SNPs with MAF≥1%, with only minor deviations in SNPs with MAF<1%. We also benchmarked the discovery capacity of BGE to access protein-coding copy number variants (CNVs) against deep whole genome data, finding that deletions and duplications spanning at least 3 exons had a positive predicted value of ~90%. Our results demonstrate BGE scalability and efficacy in capturing SNPs, indels, and CNVs in the human genome at 28% of the cost of deep whole-genome sequencing. BGE is poised to enhance access to genomic testing and empower genomic discoveries, particularly in underrepresented populations.

Phenotype harmonization and analysis for The Populations Underrepresented in Mental illness Association Studies (the PUMAS Project).

Background: The Populations Underrepresented in Mental illness Association Studies (PUMAS) project is attempting to remediate the historical underrepresentation of African and Latin American populations in psychiatric genetics through large-scale genetic association studies of individuals diagnosed with a serious mental illness [SMI, including schizophrenia (SCZ), schizoaffective disorder (SZA) bipolar disorder (BP), and severe major depressive disorder (MDD)] and matched controls. Given growing evidence indicating substantial symptomatic and genetic overlap between these diagnoses, we sought to enable transdiagnostic genetic analyses of PUMAS data by conducting phenotype alignment and harmonization for 89,320 participants (48,165 cases and 41,155 controls) from four cohorts, each of which used different ascertainment and assessment methods: PAISA n=9,105; PUMAS-LATAM n=14,638; NGAP n=42,953 and GPC n=22,624. As we describe here, these efforts have yielded harmonized datasets enabling us to analyze PUMAS genetic variation data at three levels: SMI overall, diagnoses, and individual symptoms. Methods: In aligning item-level phenotypes obtained from 14 different clinical instruments, we incorporated content, branching nature, and time frame for each phenotype; standardized diagnoses; and selected 19 core SMI item-level phenotypes for analyses. The harmonization was evaluated in PUMAS cases using multiple correspondence analysis (MCA), co-occurrence analyses, and item-level endorsement. Outcomes: We mapped >6,895 item-level phenotypes in the aggregated PUMAS data, in which SCZ (44.97%) and severe BP (BP-I, 31.53%) were the most common diagnoses. Twelve of the 19 core item-level phenotypes occurred at frequencies of > 10% across all diagnoses, indicating their potential utility for transdiagnostic genetic analyses. MCA of the 14 phenotypes that were present for all cohorts revealed consistency across cohorts, and placed MDD and SCZ into separate clusters, while other diagnoses showed no significant phenotypic clustering. Interpretation: Our alignment strategy effectively aggregated extensive phenotypic data obtained using diverse assessment tools. The MCA yielded dimensional scores which we will use for genetic analyses along with the item level phenotypes. After successful harmonization, residual phenotypic heterogeneity between cohorts reflects differences in branching structure of diagnostic instruments, recruitment strategies, and symptom interpretation (due to cultural variation).