The Mount Sinai study in Molecular Psychiatry represents an observational genetic analysis, not an RCT, drawing on Swedish national registers and NIH All of Us data to estimate 55% heritability from family patterns and 46% from common variants; whole-genome sequencing pinpointed rare HMGCR mutations while documenting overlap with bipolar disorder, schizophrenia, rheumatoid arthritis, and Sjögren’s syndrome. This work advances beyond prior candidate-gene efforts by examining rare damaging variants at scale, yet sample sizes for the sequencing arm remain modest relative to the condition’s rarity (1 in 1,000 births), and population stratification between Nordic and U.S. cohorts could influence polygenic signals. Earlier observational cohorts, such as Bergink et al. in the American Journal of Psychiatry (2015), already flagged 50–70% familial loading with bipolar disorder, but lacked genome-wide resolution; a 2022 review in Lancet Psychiatry further linked postpartum immune activation to mood episodes yet omitted cholesterol biosynthesis. HMGCR encodes the rate-limiting step in cholesterol production, a precursor for steroid hormones whose abrupt postpartum drop coincides with psychosis onset; low serum cholesterol has independently correlated with first-episode psychosis and suicidality in separate case-control studies. The autoimmune overlap aligns with clinical observations of rheumatoid arthritis and myasthenia gravis flaring or remitting after delivery, suggesting shared inflammatory mechanisms rather than purely psychiatric etiology. Mainstream coverage rarely connects these dots, focusing instead on psychosocial risk factors while underplaying the biological emergency of delusions and infanticide risk. Limitations include absence of functional validation for HMGCR variants and potential confounding by medication exposure in register data; no conflicts of interest were declared by the Mount Sinai team. These findings reposition postpartum psychosis as a predictable metabolic-immunologic vulnerability amenable to future biomarker-guided prevention.