Women are twice as likely as men to develop major depressive disorder (MDD) and are more prone to recurring episodes. Hence, we tested the hypothesis that the illness may associate with robust molecular changes in female subjects, and investigated large-scale gene expression in the postmortem brain of MDD subjects paired with matched controls (n=21 pairs). We focused on the lateral/basolateral/basomedian (LBNC) complex of the amygdala as a neural hub of mood regulation affected in MDD. Among the most robust findings were downregulated transcripts for genes coding for GABA interneuron-related peptides, including somatostatin (SST), tachykinin, neuropeptide Y (NPY) and cortistatin, in a pattern reminiscent to that previously reported in mice with low BDNF. Changes were confirmed by quantitative PCR and not explained by demographic, technical or known clinical parameters. BDNF itself was significantly downregulated at the RNA and protein levels in MDD subjects. Investigating putative mechanisms, we show that this core MDD-related gene profile (including SST, NPY, TAC1, RGS4, CORT) is recapitulated by complementary patterns in mice with constitutive (BDNF-heterozygous) or activity-dependent (Exon IV knockout) decreases in BDNF function, with a common effect on SST and NPY. Together, these results provide both direct (low RNA/protein) and indirect (low BDNF-dependent gene pattern) evidence for reduced BDNF function in the amygdala of female subjects with MDD. Supporting studies in mutant mice models suggest a complex mechanism of low constitutive and activity-dependent BDNF function in MDD, particularly affecting SST/NPY-related GABA neurons, thus linking the neurotrophic and GABA hypotheses of depression.

Background Active immunization with the BNT162b2 vaccine (Pfizer–BioNTech) has been a critical mitigation tool against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection during the coronavirus disease 2019 (Covid-19) pandemic. In light of reports of waning protection occurring 6 months after the primary two-dose vaccine series, data are needed on the safety and efficacy of offering a third (booster) dose in persons 16 years of age or older. Methods In this ongoing, placebo-controlled, randomized, phase 3 trial, we assigned participants who had received two 30-μg doses of the BNT162b2 vaccine at least 6 months earlier to be injected with a third dose of the BNT162b2 vaccine or with placebo. We assessed vaccine safety and efficacy against Covid-19 starting 7 days after the third dose. Results A total of 5081 participants received a third BNT162b2 dose and 5044 received placebo. The median interval between dose 2 and dose 3 was 10.8 months in the vaccine group and 10.7 months in the placebo group; the median follow-up was 2.5 months. Local and systemic reactogenicity events from the third dose were generally of low grade. No new safety signals were identified, and no cases of myocarditis or pericarditis were reported. Among the participants without evidence of previous SARS-CoV-2 infection who could be evaluated, Covid-19 with onset at least 7 days after dose 3 was observed in 6 participants in the vaccine group and in 123 participants in the placebo group, which corresponded to a relative vaccine efficacy of 95.3% (95% confidence interval, 89.5 to 98.3). Conclusions A third dose of the BNT162b2 vaccine administered a median of 10.8 months after the second dose provided 95.3% efficacy against Covid-19 as compared with two doses of the BNT162b2 vaccine during a median follow-up of 2.5 months. (Funded by BioNTech and Pfizer; C4591031 ClinicalTrials.gov number, NCT04955626 .)

Although circulating hormones and inhibitory gamma-aminobutyric acid (GABA)-related factors are known to affect mood, considerable knowledge gaps persist for biological mechanisms underlying the female bias in mood disorders. Here, we combine human and mouse studies to investigate sexual dimorphism in the GABA system in the context of major depressive disorder (MDD) and then use a genetic model to dissect the role of sex-related factors in GABA-related gene expression and anxiety-/depressive-like behaviors in mice. First, using meta-analysis of gene array data in human postmortem brain (N = 51 MDD subjects, 50 controls), we show that the previously reported down-regulation in MDD of somatostatin (SST), a marker of a GABA neuron subtype, is significantly greater in women with MDD. Second, using gene co-expression network analysis in control human subjects (N = 214; two frontal cortex regions) and expression quantitative trait loci mapping (N = 170 subjects), we show that expression of SST and the GABA-synthesizing enzymes glutamate decarboxylase 67 (GAD67) and GAD65 are tightly co-regulated and influenced by X-chromosome genetic polymorphisms. Third, using a rodent genetic model [Four Core Genotypes (FCG) mice], in which genetic and gonadal sex are artificially dissociated (N ≥ 12/group), we show that genetic sex (i.e., X/Y-chromosome) influences both gene expression (lower Sst, Gad67, Gad65 in XY mice) and anxiety-like behaviors (higher in XY mice). This suggests that in an intact male animal, the observed behavior represents the outcomes of male genetic sex increasing and male-like testosterone decreasing anxiety-like behaviors. Gonadal sex was the only factor influencing depressive-like behavior (gonadal males < gonadal females). Collectively, these combined human and mouse studies provide mechanistic insight into sexual dimorphism in mood disorders, and specifically demonstrate an unexpected role of male-like factors (XY genetic sex) on GABA-related genes and anxiety-like behaviors.

Genome-wide expression and genotyping technologies have uncovered the genetic bases of complex diseases at unprecedented rates. However, despite its heavy burden and high prevalence, the molecular characterization of major depressive disorder (MDD) has lagged behind. Transcriptome studies report multiple brain disturbances but are limited by small sample sizes. Genome-wide association studies (GWAS) report weak results but suggest an overlapping genetic risk with other neuropsychiatric disorders. We performed a systematic molecular characterization of altered brain function in MDD using meta-analysis of differential expression of 8 gene array studies across 3 corticolimbic brain regions in 101 subjects. The identified ‘metaA-MDD' genes suggest altered neurotrophic support, brain plasticity and neuronal signaling in MDD. Notably, metaA-MDD genes display a low connectivity and hubness in coexpression networks as well as a uniform genomic distribution, which is consistent with diffuse polygenic mechanisms. We have integrated these findings with results from over 1,800 published GWAS and show that genetic variations nearby metaA-MDD genes predict a greater risk for neuropsychiatric disorders, and notably for age-related phenotypes, but not for other medical illnesses (including those frequently co-occurring with depression) or body characteristics. Collectively, the intersection of unbiased investigations of gene function (transcriptome) and structure (GWAS) provides novel leads to investigate molecular mechanisms of MDD and suggests common biological pathways between depression, other neuropsychiatric diseases and brain aging.

BackgroundDetecting candidate markers in transcriptomic studies often encounters difficulties in complex diseases, particularly when overall signals are weak and sample size is small. Covariates including demographic, clinical and technical variables are often confounded with the underlying disease effects, which further hampers accurate biomarker detection. Our motivating example came from an analysis of five microarray studies in major depressive disorder (MDD), a heterogeneous psychiatric illness with mostly uncharacterized genetic mechanisms.ResultsWe applied a random intercept model to account for confounding variables and case-control paired design. A variable selection scheme was developed to determine the effective confounders in each gene. Meta-analysis methods were used to integrate information from five studies and post hoc analyses enhanced biological interpretations. Simulations and application results showed that the adjustment for confounding variables and meta-analysis improved detection of biomarkers and associated pathways.ConclusionsThe proposed framework simultaneously considers correction for confounding variables, selection of effective confounders, random effects from paired design and integration by meta-analysis. The approach improved disease-related biomarker and pathway detection, which greatly enhanced understanding of MDD neurobiology. The statistical framework can be applied to similar experimental design encountered in other complex and heterogeneous diseases.

Background Scavenger receptor class B type 1 (SCARB1) plays an important role in high-density lipoprotein cholesterol (HDL-C) metabolism in selective cholesteryl ester uptake and for free cholesterol cellular efflux. Methods and Results This study aims to identify common (minor allele frequency (MAF) ≥5%) and low-frequency/rare (MAF <5%) variants, using resequencing all 13 exons and exon-intron boundaries of SCARB1 in 95 individuals with extreme HDL-C levels selected from a population-based sample of 623 US non-Hispanic whites. The sequencing step identified 44 variants, of which 11 were novel with MAF <1%. Seventy-six variants (40 sequence variants, 32 common HapMap tag single nucleotide polymorphisms, and 4 relevant variants) were selected for genotyping in the total sample of 623 subjects followed by association analyses with lipid traits. Seven variants were nominally associated with apolipoprotien B (apoB) (n = 4) or HDL-C (n = 3) (P <0.05). Three variants associated with apoB remained significant after controlling false discovery rate. The most significant association was observed between rs4765615 and apoB (P = 0.0059), while rs11057844 showed the strongest association with HDL-C (P = 0.0035). A set of 17 rare variants (MAF ≤1%) showed significant association with apoB (P = 0.0284). Haplotype analysis revealed 4 regions significantly associated with either apoB or HDL-C. Conclusions Our findings provide new information about the genetic role of SCARB1 in affecting plasma apoB levels in addition to its established role in HDL-C metabolism.

Meta-analyses of European populations has successfully identified genetic variants in over 100 loci associated with lipid levels, but our knowledge in other ethnicities remains limited. To address this, we performed dense genotyping of ∼2,000 candidate genes in 7,657 African Americans, 1,315 Hispanics and 841 East Asians, using the IBC array, a custom ∼50,000 SNP genotyping array. Meta-analyses confirmed 16 lipid loci previously established in European populations at genome-wide significance level, and found multiple independent association signals within these lipid loci. Initial discovery and in silico follow-up in 7,000 additional African American samples, confirmed two novel loci: rs5030359 within ICAM1 is associated with total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) (p = 8.8×10−7 and p = 1.5×10−6 respectively) and a nonsense mutation rs3211938 within CD36 is associated with high-density lipoprotein cholesterol (HDL-C) levels (p = 13.5×10−12). The rs3211938-G allele, which is nearly absent in European and Asian populations, has been previously found to be associated with CD36 deficiency and shows a signature of selection in Africans and African Americans. Finally, we have evaluated the effect of SNPs established in European populations on lipid levels in multi-ethnic populations and show that most known lipid association signals span across ethnicities. However, differences between populations, especially differences in allele frequency, can be leveraged to identify novel signals, as shown by the discovery of ICAM1 and CD36 in the current report.

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