Research into major depressive disorder (MDD) is complicated by population heterogeneity, which has motivated the search for more homogeneous subtypes through data-driven computational methods to identify patterns in data. In addition, data on biological differences could play an important role in identifying clinically useful subtypes. This systematic review aimed to summarize evidence for biological subtypes of MDD from data-driven studies. We undertook a systematic literature search of PubMed, PsycINFO, and Embase (December 2018). We included studies that identified (1) data-driven subtypes of MDD based on biological variables, or (2) data-driven subtypes based on clinical features (e.g., symptom patterns) and validated these with biological variables post-hoc. Twenty-nine publications including 24 separate analyses in 20 unique samples were identified, including a total of ~4000 subjects. Five out of six biochemical studies indicated that there might be depression subtypes with and without disturbed neurotransmitter levels, and one indicated there might be an inflammatory subtype. Seven symptom-based studies identified subtypes, which were mainly determined by severity and by weight gain vs. loss. Two studies compared subtypes based on medication response. These symptom-based subtypes were associated with differences in biomarker profiles and functional connectivity, but results have not sufficiently been replicated. Four out of five neuroimaging studies found evidence for groups with structural and connectivity differences, but results were inconsistent. The single genetic study found a subtype with a distinct pattern of SNPs, but this subtype has not been replicated in an independent test sample. One study combining all aforementioned types of data discovered a subtypes with different levels of functional connectivity, childhood abuse, and treatment response, but the sample size was small. Although the reviewed work provides many leads for future research, the methodological differences across studies and lack of replication preclude definitive conclusions about the existence of clinically useful and generalizable biological subtypes.

Despite substantial advances in treatment and management strategies for major depression, less than 50% of patients respond to first-line antidepressant treatment or psychotherapy. Given the growing number of controlled studies of psychotherapy for treatment-resistant depression (TRD) and the preference for psychotherapy of depressed subjects as a treatment option, we conducted a meta-analysis and meta-regression analysis to investigate the effectiveness of psychotherapy for TRD. Seven different psychotherapies were studied in 21 trials that included a total of 25 comparisons. In three comparisons of psychotherapy v. treatment as usual (TAU) we found no evidence to conclude that there is a significant benefit of psychotherapy as compared with TAU. In 22 comparisons of add-on psychotherapy plus TAU v. TAU only, we found a moderate general effect size of 0.42 (95% CI 0.29-0.54) in favor of psychotherapy plus TAU. The meta-regression provided evidence for a positive association between baseline severity as well as group v. individual therapy format with the treatment effect. There was no evidence for publication bias. Most frequent investigated treatments were cognitive behavior therapy, interpersonal psychotherapy, mindfulness-based cognitive therapy, and cognitive behavioral analysis system of psychotherapy. Our meta-analysis provides evidence that, in addition to pharmacological and neurostimulatory treatments, the inclusion of add-on of psychotherapy to TAU in guidelines for the treatment of TRD is justified and will provide better outcomes for this difficult-to-treat population.

The aim of this study was to estimate the prevalence of osteopenia and osteoporosis in perimenopausal women, and to assess determinants of low bone mineral density (BMD). All women born between 1941 and 1947 (aged between 46 and 54 years) living in the city of Eindhoven were invited to participate in the study: 5896 white Dutch women, representing 73% of the total number of Dutch women in this age group, were studied. Of these, 24% were using estrogen preparations and 19% had undergone hysterectomy, with or without oophorectomy. All women were interviewed and bone mineral density (BMD) of the lumbar spine was measured by dual-energy X-ray absorptiometry (DXA). Osteopenia and osteoporosis were defined according to the criteria proposed by a WHO working group. In the population studied the prevalence of osteopenia and osteoporosis was 27.3% and 4.1%, respectively. With progression from premenopause to menopause, the prevalence of osteoporosis increased from 0.4% to 12.7%, and that of osteopenia from 14.5% to 42.8%. An increased risk for low BMD (osteopenia and osteoporosis) was associated with age, menopausal status and smoking, while alcohol consumption, high body mass index (BMI) and use of estrogens had a protective effect. This study of a large population-based cohort of perimenopausal women revealed a high prevalence of low bone mass and, therefore, a higher risk for osteoporotic fractures. The data further suggest that, when issues on the long-term efficacy and safety of preventive treatments are resolved, it may be possible to identify women at higher risk who are most likely to benefit from screening strategies.