Uganda Genome Resource Enables Insights into Population History and Genomic Discovery in Africa.

Genomic studies in African populations provide unique opportunities to understand disease etiology, human diversity, and population history. In the largest study of its kind, comprising genome-wide data from 6,400 individuals and whole-genome sequences from 1,978 individuals from rural Uganda, we find evidence of geographically correlated fine-scale population substructure. Historically, the ancestry of modern Ugandans was best represented by a mixture of ancient East African pastoralists. We demonstrate the value of the largest sequence panel from Africa to date as an imputation resource. Examining 34 cardiometabolic traits, we show systematic differences in trait heritability between European and African populations, probably reflecting the differential impact of genes and environment. In a multi-trait pan-African GWAS of up to 14,126 individuals, we identify novel loci associated with anthropometric, hematological, lipid, and glycemic traits. We find that several functionally important signals are driven by Africa-specific variants, highlighting the value of studying diverse populations across the region.

Ancestry-specific high-risk gene variant profiling unmasks diabetes-associated genes.

How ancestry-associated genetic variance affects disparities in the risk for polygenic diseases and influences the identification of disease-associated genes warrant a deeper understanding. We hypothesized that the discovery of genes associated with polygenic diseases may be limited by overreliance on single-nucleotide polymorphism (SNP)-based genomic investigation, since most significant variants identified in genome-wide SNP association studies map to introns and intergenic regions of the genome. To overcome such potential limitation, we developed a gene-constrained and function-based analytical method centered on high-risk variants (hrV) that encode frameshifts, stopgains, or splice site disruption. We analyzed the total number of hrV per gene in populations of different ancestry, representing a total of 185 934 subjects. Using this analysis, we developed a quantitative index of hrV (hrVI) across 20 428 genes within each population. We then applied hrVI analysis to the discovery of genes associated with type 2 diabetes mellitus (T2DM), a polygenic disease with ancestry-related disparity. HrVI profiling and gene-to-gene comparisons of ancestry-specific hrV between the case (20 781 subjects) and control (24 440 subjects) populations in the T2DM national repository identified 57 genes associated with T2DM, 40 of which were discoverable only by ancestry-specific analysis. These results illustrate how function-based and ancestry-specific analysis of genetic variations can accelerate the identification of genes associated with polygenic diseases. Besides T2DM, such analysis may facilitate our understanding of the genetic basis for other polygenic diseases that are also greatly influenced by environmental and behavioral factors, such as obesity, hypertension, and Alzheimer's disease.

Discovery and fine-mapping of height loci via high-density imputation of GWASs in individuals of African ancestry.

Although many loci have been associated with height in European ancestry populations, very few have been identified in African ancestry individuals. Furthermore, many of the known loci have yet to be generalized to and fine-mapped within a large-scale African ancestry sample. We performed sex-combined and sex-stratified meta-analyses in up to 52,764 individuals with height and genome-wide genotyping data from the African Ancestry Anthropometry Genetics Consortium (AAAGC). We additionally combined our African ancestry meta-analysis results with published European genome-wide association study (GWAS) data. In the African ancestry analyses, we identified three novel loci (SLC4A3, NCOA2, ECD/FAM149B1) in sex-combined results and two loci (CRB1, KLF6) in women only. In the African plus European sex-combined GWAS, we identified an additional three novel loci (RCCD1, G6PC3, CEP95) which were equally driven by AAAGC and European results. Among 39 genome-wide significant signals at known loci, conditioning index SNPs from European studies identified 20 secondary signals. Two of the 20 new secondary signals and none of the 8 novel loci had minor allele frequencies (MAF) < 5%. Of 802 known European height signals, 643 displayed directionally consistent associations with height, of which 205 were nominally significant (p < 0.05) in the African ancestry sex-combined sample. Furthermore, 148 of 241 loci contained ≤20 variants in the credible sets that jointly account for 99% of the posterior probability of driving the associations. In summary, trans-ethnic meta-analyses revealed novel signals and further improved fine-mapping of putative causal variants in loci shared between African and European ancestry populations.

Preventing post-discharge suicides in psychiatric patients: insights from patients, lay healthcare supporters, and mental health professionals-a qualitative analysis.

BACKGROUND: Discharged psychiatric patients are at higher risk of suicide due to various risk factors in their lives compared to the general population. However, specific problems and needs of these patients after discharge remain unclear. This research constitutes a segment of a broader implementation study designed to formulate an interventional strategy targeting post-discharge suicide among Chinese psychiatric patients. The present study seeks to qualitatively investigate the problems and needs from the perspectives of patients, their lay healthcare supporters (LHSs), and mental health professionals (MPs), aiming to enhance the efficacy of the interventional strategy. METHODS: This study is part of a larger implementation study based on Shenzhen Kangning Hospital (SKH) in Shenzhen, Guangdong, China. Under the community-based participatory research framework, we recruited discharged psychiatric patients, their LHSs, and MPs as a collaborative community team, and we conducted individual in-depth interviews for patients and LSHs and focus group interviews with MPs. We utilized a thematic analysis approach to identify sub-themes and themes from interviews through systematically coding and analyzing the data. RESULTS: A total of 45 participants were recruited for interviews, comprising 17 patients, 8 LHSs, and 20 MPs. We conducted 25 individual in-depth interviews and 3 focus group interviews. Through the interviews, we identified three themes of post-discharge problems: problems related to self, family-related problems, societal and community-related problems. We also identified four themes related to reducing post-discharge suicide: proactive self-management, multifunctional relatives, multifunctional MP group, and a warm society. The tangible support from LHSs and emotional support from MPs are strongly emphasized. Follow-up interventions were identified as the most significant way to addressing these unmet needs. Instrumental support from the community and a caring and non-discriminatory environment for individuals with mental disorders are essential for reducing suicide risk. CONCLUSIONS: Establishing an integrated mental health care service network that connects psychiatric patients, LHSs, and MPs cross community and societal sectors, with patient-centered follow-up care at its core, is a practical approach to better address patients' needs and reduce post-discharge suicide. TRIAL REGISTRATION: Registration number: NCT04907669. Date of registration: May 26th,2021.

GWAS in Africans identifies novel lipids loci and demonstrates heterogenous association within Africa.

Serum lipids are biomarkers of cardiometabolic disease risk, and understanding genomic factors contributing to their distribution is of interest. Studies of lipids in Africans are rare, though it is expected that such studies could identify novel loci. We conducted a GWAS of 4317 Africans enrolled from Nigeria, Ghana and Kenya. We evaluated linear mixed models of high-density lipoprotein cholesterol (HDLC), low-density lipoprotein cholesterol (LDLC), total cholesterol (CHOL), triglycerides (TG) and TG/HDLC. Replication was attempted in 9542 African Americans (AA). In our main analysis, we identified 28 novel associations in Africans. Of the 18 of these that could be tested in AA, three associations replicated (GPNMB-TG, ENPP1-TG and SMARCA4-LDLC). Five additional novel loci were discovered upon meta-analysis with AA (rs138282551-TG, PGBD5-HDLC, CD80-TG/HDLC, SLC44A1-CHOL and TLL2-CHOL). Analyses considering only those with predominantly West African ancestry (Nigeria, Ghana and AA) yielded new insights: ORC5-LDLC and chr20:60973327-CHOL. Among our novel findings are some loci with known connections to lipids pathways. For instance, rs147706369 (TLL2) alters a regulatory motif for sterol regulatory element-binding proteins, a family of transcription factors that control the expression of a range of enzymes involved in cholesterol, fatty acid and TG synthesis, and rs115749422 (SMARCA4), an independent association near the known LDLR locus that is rare or absent in populations without African ancestry. These findings demonstrate the utility of conducting genomic analyses in Africans for discovering novel loci and provide some preliminary evidence for caution against treating 'African ancestry' as a monolithic category.

An adaptive direction-assisted test for microbiome compositional data.

MOTIVATION: Microbial communities have been shown to be associated with many complex diseases, such as cancers and cardiovascular diseases. The identification of differentially abundant taxa is clinically important. It can help understand the pathology of complex diseases, and potentially provide preventive and therapeutic strategies. Appropriate differential analyses for microbiome data are challenging due to its unique data characteristics including compositional constraint, excessive zeros and high dimensionality. Most existing approaches either ignore these data characteristics or only account for the compositional constraint by using log-ratio transformations with zero observations replaced by a pseudocount. However, there is no consensus on how to choose a pseudocount. More importantly, ignoring the characteristic of excessive zeros may result in poorly powered analyses and therefore yield misleading findings. RESULTS: We develop a novel microbiome-based direction-assisted test for the detection of overall difference in microbial relative abundances between two health conditions, which simultaneously incorporates the characteristics of relative abundance data. The proposed test (i) divides the taxa into two clusters by the directions of mean differences of relative abundances and then combines them at cluster level, in light of the compositional characteristic; and (ii) contains a burden type test, which collapses multiple taxa into a single one to account for excessive zeros. Moreover, the proposed test is an adaptive procedure, which can accommodate high-dimensional settings and yield high power against various alternative hypotheses. We perform extensive simulation studies across a wide range of scenarios to evaluate the proposed test and show its substantial power gain over some existing tests. The superiority of the proposed approach is further demonstrated with real datasets from two microbiome studies. AVAILABILITY AND IMPLEMENTATION: An R package for MiDAT is available at https://github.com/zhangwei0125/MiDAT. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Divalent Heterometal Doped Titanium-Oxide Cluster Polymers: Structures, Photoresponse, and Photocatalysis.

Five cluster polymers based on heterometal-doped titanium-oxide cluster (TOC) monomers are reported. The monomers feature Ti10-oxide cluster cores and are connected to the divalent closed-shell heterometal anchors by salicylate ligands. The Sr2+, Ba2+, and Pb2+ dopants cause the monomers to bind head-to-head and generate linear chains, while the Ca2+ and Cd2+ lead to head-to-tail connections and zigzag chains. The cluster polymers are responsive to visible-light up to 565 nm and photo-catalytically active in both H2 evolution and CO2/epoxide cycloaddition reactions. The photo-absorption, photo-charge separation, and photocatalytic properties of the cluster polymers are dependent on the heterometal dopants in order Cd > Pb > Ba > Sr > Ca. Heterometals serve as the catalytic sites in the cluster polymers, which depending on the contribution of the pCB bottom, facilitate photo-charge separation and interfacial charge transfer, further enhancing catalytic activity. The tunable compositions and topologies of the cluster polymers shown herein may inspire the design and synthesis of more multidimensional functional metal-oxide cluster materials for a variety of applications in the future.

Ligation of Titanium-oxide and {Mo2} Units for Solar CO2 Storage.

Two Mo-Ti-mixed oxide clusters, Ti6Mo4 and Ti4Mo4, which contain the {Mo2V} unit commonly observed in many polyoxomolybdates, were successfully synthesized. The introduction of a {Mo2V} dopant into a titanium-oxide cluster (TOC) results in a red shift of the absorption edge, hence leading to a substantial enhancement of visible-light absorption. The band gap electron transition mainly involves the ligand-to-metal charge transfer (LMCT, benzoate-to-Mo) and MoV d-d transition. Both clusters show favorable visible-light responsiveness and charge-separation efficiency. Both serve as heterogeneous photocatalysts and exhibit excellent catalytic activity in CO2/epoxide cycloadditions under very mild conditions. The mechanism study suggests that the catalytically active sites are mainly MoV, and the photogenerated electrons and holes are both involved. Ti6Mo4 exhibits better photocatalytic activity than Ti4Mo4, demonstrating the crucial role of the titanium-oxide core, which corresponds to improved light absorption and charge-separation efficiency. Our findings highlight the potential of the {Mo2V} unit in constructing Mo-Ti-mixed oxide clusters with interesting topologies and excellent solar-light-harvesting activity.

Light Scattering of Electrospinning Jet with Internal Structures by Flow-Induced Phase Separation.

Herein, the direct morphological evidence of the extension-induced phase-separated structures in the electrospinning jet observed by high-speed video imaging and by light scattering technique is reported. Model solutions of poly(vinyl alcohol) (PVA)/water are electrospun. Two types of internal structures, that is, long strings and short ellipsoids, are found. A light scattering model is derived for the Vv scattering configuration to account for the scattered intensities contributed from the liquid jet itself and those from the internal structures. For the severely stretching jet of PVA/water, the Vv intensity profile is dominant by the internal structures to mask the scattering contribution from the jet itself. Moreover, the Hv intensity profile reflects the anisotropy of the oriented chains parallel to the jet axis. For the 7 wt% solution, the derived extension rate in the vicinity of the Taylor cone apex is about 3420 s-1 , which is higher than the Rouse relaxation rate measured by rheometer. It is concluded that extension-induced phase separation of the single-phase PVA solution is likely to occur in Taylor-cone apex to trigger the self-assembly process for producing strings (and/or bulges) in the flowing jet, which eventually transform to become the nanofibers, after solvent removal, to be collected on the grounded collector.

Refining genome-wide associated loci for serum uric acid in individuals with African ancestry.

OBJECTIVE: Serum uric acid is the end-product of purine metabolism and at high levels is a risk factor for several human diseases including gout and cardiovascular disease. Heritability estimates range from 0.32 to 0.63. Genome-wide association studies (GWAS) provide an unbiased approach to identify loci influencing serum uric acid. Here, we performed the first GWAS for serum uric acid in continental Africans, with replication in African Americans. METHODS: Africans (n = 4126) and African Americans (n = 5007) were genotyped on high-density GWAS arrays. Efficient mixed model association, a variance component approach, was used to perform association testing for a total of ~ 18 million autosomal genotyped and imputed variants. CAVIARBF was used to fine map significant regions. RESULTS: We identified two genome-wide significant loci: 4p16.1 (SLC2A9) and 11q13.1 (SLC22A12). At SLC2A9, the most strongly associated SNP was rs7683856 (P = 1.60 × 10-44). Conditional analysis revealed a second signal indexed by rs6838021 (P = 5.75 × 10-17). Gene expression and regulatory motif data prioritized a single-candidate causal variant for each signal. At SLC22A12, the most strongly associated SNP was rs147647315 (P = 6.65 × 10-25). Conditional analysis and functional annotation prioritized the missense variant rs147647315 (R (Arg) > H (His)) as the sole causal variant. Functional annotation of these three signals implicated processes in skeletal muscle, subcutaneous adipose tissue and the kidneys, respectively. CONCLUSIONS: This first GWAS of serum uric acid in continental Africans identified three associations at two loci, SLC2A9 and SLC22A12. The combination of weak linkage disequilibrium in Africans and functional annotation led to the identification of candidate causal SNPs for all three signals. Each candidate causal variant implicated a different cell type. Collectively, the three associations accounted for 4.3% of the variance of serum uric acid.

Development of a Practical Screening Tool to Predict Sarcopenia in Patients on Maintenance Hemodialysis.

BACKGROUND Sarcopenia is a common complication in maintenance hemodialysis (MHD) and can increase patient hospitalization and mortality. No simple and reliable tools to identify sarcopenia exist. We aimed to develop a screening tool to predict MHD patients at high risk for sarcopenia. MATERIAL AND METHODS This cross-sectional study included 589 and 216 MHD patients for training and validation sets, respectively. We used diagnostic criteria developed by the Asian Working Group on Sarcopenia to screen for sarcopenia. The risk prediction model was established by univariate and multivariate logistic regression analyses. We used the area under the receiver operating characteristic curve (AUROC), calibration curve, Hosmer-Lemeshow test, and decision curve analysis (DCA) to evaluate the model's discrimination ability, calibration ability, and clinical utility. RESULTS The incidence of sarcopenia was 17.1% in the training set and 18.1% in the validation set. We constructed prediction models applying age, body mass index, calf circumference, and serum creatinine and plotted a nomogram. The training set model had an AUROC of 0.922, sensitivity of 85.1%, specificity of 85.9%, and chi-square value (Hosmer-Lemeshow test) of 5.603 (P>0.05); the DCA diagram showed that when the threshold probability was 0 to 0.95, the model predicted a net benefit for sarcopenia in MHD patients. The validation set model had an AUROC of 0.913, sensitivity of 94.3%, specificity of 82.9%, and chi-square value (Hosmer-Lemeshow test) of 9.822 (P>0.05). CONCLUSIONS The screening tool has good discrimination ability, calibration ability, and clinical utility. It could help to identify MHD patients at a high risk for sarcopenia.

Correction: Single-trait and multi-trait genome-wide association analyses identify novel loci for blood pressure in African-ancestry populations.

[This corrects the article DOI: 10.1371/journal.pgen.1006728.].

Acceptability of Acute and Maintenance Pharmacotherapy of Bipolar Disorder: A Systematic Review of Randomized, Double-Blind, Placebo-Controlled Clinical Trials.

PURPOSE/BACKGROUND: The aim of the study was to estimate and rank the risk for the discontinuation due to adverse events (DAEs), 7% or more weight gain (WG), and somnolence during the acute and maintenance treatment of bipolar disorder with a mood stabilizer or an antipsychotic monotherapy. METHODS/PROCEDURES: The search of MEDLINE, EMBASE, PsycINFO, and clinicaltrials.gov from the inception to December 31, 2018, provided 32 studies in mania, 16 in bipolar depression, and 13 in maintenance. Data of DAEs, WG, and somnolence from each study were extracted. The risk for these variables of an active treatment relative to placebo was estimated with a number needed to harm (NNH) as a single study and pooled sample. FINDINGS/RESULTS: For DAEs, pooled NNH ranged from 19 with carbamazepine to -21 with quetiapine-XR in mania, 11 with quetiapine-IR 600 mg/d to -37 with olanzapine/fluoxetine combination in bipolar depression, and 5 with lithium to -8 with asenapine in maintenance. For WG, pooled NNH ranged from 9 with olanzapine to -78 with aripiprazole in mania, 5 with olanzapine to -112 with lithium in bipolar depression, and 4 with olanzapine to 126 with asenapine in maintenance. For somnolence, pooled NNH was from 5 with carbamazepine to 23 with cariprazine in mania, 3 with quetiapine-XR 300 mg/d to 79 with lurasidone in bipolar depression, and 11 with olanzapine to -49 with aripiprazole in maintenance. IMPLICATIONS/CONCLUSIONS: All medications studied in bipolar disorder were relatively well tolerated during different phases of treatment; however, the risk for short- and long-term WG and somnolence varied widely among included psychotropics.

Discovery and fine-mapping of adiposity loci using high density imputation of genome-wide association studies in individuals of African ancestry: African Ancestry Anthropometry Genetics Consortium.

Genome-wide association studies (GWAS) have identified >300 loci associated with measures of adiposity including body mass index (BMI) and waist-to-hip ratio (adjusted for BMI, WHRadjBMI), but few have been identified through screening of the African ancestry genomes. We performed large scale meta-analyses and replications in up to 52,895 individuals for BMI and up to 23,095 individuals for WHRadjBMI from the African Ancestry Anthropometry Genetics Consortium (AAAGC) using 1000 Genomes phase 1 imputed GWAS to improve coverage of both common and low frequency variants in the low linkage disequilibrium African ancestry genomes. In the sex-combined analyses, we identified one novel locus (TCF7L2/HABP2) for WHRadjBMI and eight previously established loci at P < 5×10-8: seven for BMI, and one for WHRadjBMI in African ancestry individuals. An additional novel locus (SPRYD7/DLEU2) was identified for WHRadjBMI when combined with European GWAS. In the sex-stratified analyses, we identified three novel loci for BMI (INTS10/LPL and MLC1 in men, IRX4/IRX2 in women) and four for WHRadjBMI (SSX2IP, CASC8, PDE3B and ZDHHC1/HSD11B2 in women) in individuals of African ancestry or both African and European ancestry. For four of the novel variants, the minor allele frequency was low (<5%). In the trans-ethnic fine mapping of 47 BMI loci and 27 WHRadjBMI loci that were locus-wide significant (P < 0.05 adjusted for effective number of variants per locus) from the African ancestry sex-combined and sex-stratified analyses, 26 BMI loci and 17 WHRadjBMI loci contained ≤ 20 variants in the credible sets that jointly account for 99% posterior probability of driving the associations. The lead variants in 13 of these loci had a high probability of being causal. As compared to our previous HapMap imputed GWAS for BMI and WHRadjBMI including up to 71,412 and 27,350 African ancestry individuals, respectively, our results suggest that 1000 Genomes imputation showed modest improvement in identifying GWAS loci including low frequency variants. Trans-ethnic meta-analyses further improved fine mapping of putative causal variants in loci shared between the African and European ancestry populations.

Single-trait and multi-trait genome-wide association analyses identify novel loci for blood pressure in African-ancestry populations.

Hypertension is a leading cause of global disease, mortality, and disability. While individuals of African descent suffer a disproportionate burden of hypertension and its complications, they have been underrepresented in genetic studies. To identify novel susceptibility loci for blood pressure and hypertension in people of African ancestry, we performed both single and multiple-trait genome-wide association analyses. We analyzed 21 genome-wide association studies comprised of 31,968 individuals of African ancestry, and validated our results with additional 54,395 individuals from multi-ethnic studies. These analyses identified nine loci with eleven independent variants which reached genome-wide significance (P < 1.25×10-8) for either systolic and diastolic blood pressure, hypertension, or for combined traits. Single-trait analyses identified two loci (TARID/TCF21 and LLPH/TMBIM4) and multiple-trait analyses identified one novel locus (FRMD3) for blood pressure. At these three loci, as well as at GRP20/CDH17, associated variants had alleles common only in African-ancestry populations. Functional annotation showed enrichment for genes expressed in immune and kidney cells, as well as in heart and vascular cells/tissues. Experiments driven by these findings and using angiotensin-II induced hypertension in mice showed altered kidney mRNA expression of six genes, suggesting their potential role in hypertension. Our study provides new evidence for genes related to hypertension susceptibility, and the need to study African-ancestry populations in order to identify biologic factors contributing to hypertension.

Genome-wide association study of type 2 diabetes in Africa.

AIMS/HYPOTHESIS: Genome-wide association studies (GWAS) for type 2 diabetes have uncovered >400 risk loci, primarily in populations of European and Asian ancestry. Here, we aimed to discover additional type 2 diabetes risk loci (including African-specific variants) and fine-map association signals by performing genetic analysis in African populations. METHODS: We conducted two type 2 diabetes genome-wide association studies in 4347 Africans from South Africa, Nigeria, Ghana and Kenya and meta-analysed both studies together. Likely causal variants were identified using fine-mapping approaches. RESULTS: The most significantly associated variants mapped to the widely replicated type 2 diabetes risk locus near TCF7L2 (p = 5.3 × 10-13). Fine-mapping of the TCF7L2 locus suggested one type 2 diabetes association signal shared between Europeans and Africans (indexed by rs7903146) and a distinct African-specific signal (indexed by rs17746147). We also detected one novel signal, rs73284431, near AGMO (p = 5.2 × 10-9, minor allele frequency [MAF] = 0.095; monomorphic in most non-African populations), distinct from previously reported signals in the region. In analyses focused on 100 published type 2 diabetes risk loci, we identified 21 with shared causal variants in African and non-African populations. CONCLUSIONS/INTERPRETATION: These results demonstrate the value of performing GWAS in Africans, provide a resource to larger consortia for further discovery and fine-mapping and indicate that additional large-scale efforts in Africa are warranted to gain further insight in to the genetic architecture of type 2 diabetes.

Enzymatic activity of palmitoyl-protein thioesterase-1 in serum from schizophrenia significantly associates with schizophrenia diagnosis scales.

Genome-wide association studies have confirmed that schizophrenia is an inheritable multiple-gene mental disorder. Longitudinal studies about depression, first episode psychosis (FEP) and acute psychotic relapse have mostly searched for brain imaging biomarkers and inflammatory markers from the blood. However, to the best of our knowledge, the association between enzymatic activities with diagnosis or prediction of treatment response in people with schizophrenia has barely been validated. Under the Longitudinal Study of National Mental Health Work Plan (2015-2020), we have studied a subsample of approximately 36 individuals from the cohort with data on palmitoyl-protein thioesterase-1 enzymatic activity from FEP and performed a bivariate correlation analysis with psychiatric assessment scores. After adjusting for sex, age, body mass index (BMI) and total serum protein, our data demonstrated that PPT1 enzymatic activity is significantly associated with schizophrenia and its Positive and Negative Syndrome Scale (PANSS) scores. This longitudinal study compared the PPT1 enzymatic activity in FEP schizophrenia patients and healthy volunteers, and the former exhibited a significant 1.5-fold increase in PPT1 enzymatic levels (1.79 mmol/L/h/mL, and 1.18 mmol/L/h/mL; P < 0.05; 95% CI, 2.3-2.9 and 1.4-1.8). The higher PPT1 enzymatic levels in FEP schizophrenia patients were positively associated with larger PANSS scaling scores (r = 0.32, P = 0.0079 for positive scaling; r = 0.41, P = 0.0006 for negative scaling; r = 0.45, P = 0.0001 for general scaling; and r = 0.34, P = 0.0048 for PNASS-S scaling). Higher enzymatic PPT1 in FEP schizophrenia patients is significantly associated with increased PANSS scaling values, indicating more serious rates of developing psychosis. Enzymatic activity of PPT1 may provide an important new view for schizophrenia disorders.

The genomic landscape of African populations in health and disease.

A deeper appreciation of the complex architecture of African genomes is critical to the global effort to understand human history, biology and differential distribution of disease by geography and ancestry. Here, we report on how the growing engagement of African populations in genome science is providing new insights into the forces that shaped human genomes before and after the Out-of-Africa migrations. As a result of this human evolutionary history, African ancestry populations have the greatest genomic diversity in the world, and this diversity has important ramifications for genomic research. In the case of pharmacogenomics, for instance, variants of consequence are not limited to those identified in other populations, and diversity within African ancestry populations precludes summarizing risk across different African ethnic groups. Exposure of Africans to fatal pathogens, such as Plasmodium falciparum, Lassa Virus and Trypanosoma brucei rhodesiense, has resulted in elevated frequencies of alleles conferring survival advantages for infectious diseases, but that are maladaptive in modern-day environments. Illustrating with cardiometabolic traits, we show that while genomic research in African ancestry populations is still in early stages, there are already many examples of novel and African ancestry-specific disease loci that have been discovered. Furthermore, the shorter haplotypes in African genomes have facilitated fine-mapping of loci discovered in other human ancestry populations. Given the insights already gained from the interrogation of African genomes, it is imperative to continue and increase our efforts to describe genomic risk in and across African ancestry populations.

Measuring gene-gene interaction using Kullback-Leibler divergence.

Genome-wide association studies (GWAS) are used to investigate genetic variants contributing to complex traits. Despite discovering many loci, a large proportion of "missing" heritability remains unexplained. Gene-gene interactions may help explain some of this gap. Traditionally, gene-gene interactions have been evaluated using parametric statistical methods such as linear and logistic regression, with multifactor dimensionality reduction (MDR) used to address sparseness of data in high dimensions. We propose a method for the analysis of gene-gene interactions across independent single-nucleotide polymorphisms (SNPs) in two genes. Typical methods for this problem use statistics based on an asymptotic chi-squared mixture distribution, which is not easy to use. Here, we propose a Kullback-Leibler-type statistic, which follows an asymptotic, positive, normal distribution under the null hypothesis of no relationship between SNPs in the two genes, and normally distributed under the alternative hypothesis. The performance of the proposed method is evaluated by simulation studies, which show promising results. The method is also used to analyze real data and identifies gene-gene interactions among RAB3A, MADD, and PTPRN on type 2 diabetes (T2D) status.

Trans-ethnic Meta-analysis and Functional Annotation Illuminates the Genetic Architecture of Fasting Glucose and Insulin.

Knowledge of the genetic basis of the type 2 diabetes (T2D)-related quantitative traits fasting glucose (FG) and insulin (FI) in African ancestry (AA) individuals has been limited. In non-diabetic subjects of AA (n = 20,209) and European ancestry (EA; n = 57,292), we performed trans-ethnic (AA+EA) fine-mapping of 54 established EA FG or FI loci with detailed functional annotation, assessed their relevance in AA individuals, and sought previously undescribed loci through trans-ethnic (AA+EA) meta-analysis. We narrowed credible sets of variants driving association signals for 22/54 EA-associated loci; 18/22 credible sets overlapped with active islet-specific enhancers or transcription factor (TF) binding sites, and 21/22 contained at least one TF motif. Of the 54 EA-associated loci, 23 were shared between EA and AA. Replication with an additional 10,096 AA individuals identified two previously undescribed FI loci, chrX FAM133A (rs213676) and chr5 PELO (rs6450057). Trans-ethnic analyses with regulatory annotation illuminate the genetic architecture of glycemic traits and suggest gene regulation as a target to advance precision medicine for T2D. Our approach to utilize state-of-the-art functional annotation and implement trans-ethnic association analysis for discovery and fine-mapping offers a framework for further follow-up and characterization of GWAS signals of complex trait loci.