The genetics of the mood disorder spectrum:genome-wide association analyses of over 185,000 cases and 439,000 controls

Background Mood disorders (including major depressive disorder and bipolar disorder) affect 10-20% of the population. They range from brief, mild episodes to severe, incapacitating conditions that markedly impact lives. Despite their diagnostic distinction, multiple approaches have shown considerable sharing of risk factors across the mood disorders. Methods To clarify their shared molecular genetic basis, and to highlight disorder-specific associations, we meta-analysed data from the latest Psychiatric Genomics Consortium (PGC) genome-wide association studies of major depression (including data from 23andMe) and bipolar disorder, and an additional major depressive disorder cohort from UK Biobank (total: 185,285 cases, 439,741 controls; non-overlapping N = 609,424). Results Seventy-three loci reached genome-wide significance in the meta-analysis, including 15 that are novel for mood disorders. More genome-wide significant loci from the PGC analysis of major depression than bipolar disorder reached genome-wide significance. Genetic correlations revealed that type 2 bipolar disorder correlates strongly with recurrent and single episode major depressive disorder. Systems biology analyses highlight both similarities and differences between the mood disorders, particularly in the mouse brain cell-types implicated by the expression patterns of associated genes. The mood disorders also differ in their genetic correlation with educational attainment – positive in bipolar disorder but negative in major depressive disorder. Conclusions The mood disorders share several genetic associations, and can be combined effectively to increase variant discovery. However, we demonstrate several differences between these disorders. Analysing subtypes of major depressive disorder and bipolar disorder provides evidence for a genetic mood disorders spectrum

Genetic Overlap Between Alzheimer’s Disease and Bipolar Disorder Implicates the MARK2 and VAC14 Genes

Background: Alzheimer's disease (AD) and bipolar disorder (BIP) are complex traits influenced by numerous common genetic variants, most of which remain to be detected. Clinical and epidemiological evidence suggest that AD and BIP are related. However, it is not established if this relation is of genetic origin. Here, we applied statistical methods based on the conditional false discovery rate (FDR) framework to detect genetic overlap between AD and BIP and utilized this overlap to increase the power to identify common genetic variants associated with either or both traits. Methods: We obtained genome wide association studies data from the International Genomics of Alzheimer's Project part 1 (17,008 AD cases and 37,154 controls) and the Psychiatric Genetic Consortium Bipolar Disorder Working Group (20,352 BIP cases and 31,358 controls). We used conditional QQ-plots to assess overlap in common genetic variants between AD and BIP. We exploited the genetic overlap to re-rank test-statistics for AD and BIP and improve detection of genetic variants using the conditional FDR framework. Results: Conditional QQ-plots demonstrated a polygenic overlap between AD and BIP. Using conditional FDR, we identified one novel genomic locus associated with AD, and nine novel loci associated with BIP. Further, we identified two novel loci jointly associated with AD and BIP implicating the MARK2 gene (lead SNP rs10792421, conjunctional FDR=0.030, same direction of effect) and the VAC14 gene (lead SNP rs11649476, conjunctional FDR=0.022, opposite direction of effect). Conclusions: We found polygenic overlap between AD and BIP and identified novel loci for each trait and two jointly associated loci. Further studies should examine if the shared loci implicating the MARK2 and VAC14 genes could explain parts of the shared and distinct features of AD and BIP

Bipolar multiplex families have an increased burden of common risk variants for psychiatric disorders.

Multiplex families with a high prevalence of a psychiatric disorder are often examined to identify rare genetic variants with large effect sizes. In the present study, we analysed whether the risk for bipolar disorder (BD) in BD multiplex families is influenced by common genetic variants. Furthermore, we investigated whether this risk is conferred mainly by BD-specific risk variants or by variants also associated with the susceptibility to schizophrenia or major depression. In total, 395 individuals from 33 Andalusian BD multiplex families (166 BD, 78 major depressive disorder, 151 unaffected) as well as 438 subjects from an independent, BD case/control cohort (161 unrelated BD, 277 unrelated controls) were analysed. Polygenic risk scores (PRS) for BD, schizophrenia (SCZ), and major depression were calculated and compared between the cohorts. Both the familial BD cases and unaffected family members had higher PRS for all three psychiatric disorders than the independent controls, with BD and SCZ being significant after correction for multiple testing, suggesting a high baseline risk for several psychiatric disorders in the families. Moreover, familial BD cases showed significantly higher BD PRS than unaffected family members and unrelated BD cases. A plausible hypothesis is that, in multiplex families with a general increase in risk for psychiatric disease, BD development is attributable to a high burden of common variants that confer a specific risk for BD. The present analyses demonstrated that common genetic risk variants for psychiatric disorders are likely to contribute to the high incidence of affective psychiatric disorders in the multiplex families. However, the PRS explained only part of the observed phenotypic variance, and rare variants might have also contributed to disease development

Genomic Dissection of Bipolar Disorder and Schizophrenia, Including 28 Subphenotypes

Schizophrenia and bipolar disorder are two distinct diagnoses that share symptomology. Understanding the genetic factors contributing to the shared and disorder-specific symptoms will be crucial for improving diagnosis and treatment. In genetic data consisting of 53,555 cases (20,129 bipolar disorder [BD], 33,426 schizophrenia [SCZ]) and 54,065 controls, we identified 114 genome-wide significant loci implicating synaptic and neuronal pathways shared between disorders. Comparing SCZ to BD (23,585 SCZ, 15,270 BD) identified four genomic regions including one with disorder-independent causal variants and potassium ion response genes as contributing to differences in biology between the disorders. Polygenic risk score (PRS) analyses identified several significant correlations within case-only phenotypes including SCZ PRS with psychotic features and age of onset in BD. For the first time, we discover specific loci that distinguish between BD and SCZ and identify polygenic components underlying multiple symptom dimensions. These results point to the utility of genetics to inform symptomology and potential treatment

RT-qPCR versus Digital PCR: How Do They Impact Differently on Clinical Management of Chronic Myeloid Leukemia Patients?

Real-time quantitative PCR (RT-qPCR) is the gold standard to quantify the BCR-ABL1 transcript for molecular response monitoring in chronic myeloid leukemia (CML) patients, and it plays a pivotal role in clinical decision-making process, even if it presents technical limits. Increasing data suggest that digital PCR (dPCR) is more accurate and reliable than RT-qPCR in CML minimal residual disease monitoring and in patients’ selection for treatment discontinuation. But what about the identification of treatment discontinuation failures? We present the case of a CML patient enrolled both in a study aiming to comparatively assess molecular response by RT-qPCR and dPCR and in the progressive arm of the OPTkIMA trial. This is a phase III trial including CML patients randomized to receive a fixed versus a progressive intermittent tyrosine kinase inhibitor regimen. At 24 months, because of two consecutive detections of MR2.0 by RT-qPCR, the patient resumed daily treatment. Conversely, dPCR revealed a stability of molecular response and even a slight decreasing of transcript over time. An additional specimen was sampled one month after the first MR2.0 detection because of clinical decision: RT-qPCR resulted MR3.0 and dPCR confirmed the transcript’s stability. Nowadays, the resumption of therapy is RT-qPCR-driven despite its limits in detection and robustness. In this case, according to dPCR, the patient could have continued intermittent treatment and the stability of response was then confirmed by RT-qPCR. So, dPCR could be able to better identify peculiar clinical response to therapy

Multidimensional geriatric assessment for elderly hematological patients (≥60 years) submitted to allogeneic stem cell transplantation. A French-Italian 10-year experience on 228 patients

Nowadays, the evaluation of elderly patients' eligibility for allogeneic stem cell transplantation (allo-SCT) is crucial. We evaluated the feasibility and efficacy of a multidimensional geriatric assessment, the Fondazione Italiana Linfomi (FIL) score, on a cohort of 228 patients older than 60 years submitted to allo-SCT in Italy and France from 2008 to 2018. Based on FIL score, available in 215 patients, 125 (58%) patients were classified as "fit" and 90 as "unfit/frail." The hematopoietic cell transplantation-specific comorbidity index (HCT-CI) was measured in 222 patients (97%); 71 (32%) patients had HCT-CI 0, 75 (34%) patients scored 1-2, and 76 (34%) ≥3. A total of 121 (53%) patients died after a median follow-up of 36 months. FIL score was found to highly predict survival, due to an excess of NRM in unfit/frail group, and confirmed its independent prognostic role on OS (HR: 0.37; 95% CI: 0.25-0.55; p < 0.0001). On the contrary, the HCI-CI failed in allo-SCT outcome prediction (HR: 1.06; 95% CI: 0.96-1.16; p = 0.27). In summary, a comprehensive geriatric assessment with FIL score seems to add significant prognostic information in elderly patients submitted to allo-SCT. The pretransplant adoption of this easy-to-use tool could help the patients' selection and management

Case Report: Late Onset of Myelodysplastic Syndrome From Donor Progenitor Cells After Allogeneic Stem Cell Transplantation. Which Lessons Can We Draw From the Reported Case?

Background: Myelodysplastic syndromes and acute leukemias after allogeneic stem cell transplantation (allo-SCT) are mainly caused by recurrence of the primitive leukemic clones. More rarely, they originate from donor hematopoietic stem cells, developing the so-called donor cell leukemia (DCL) or myelodysplastic syndromes (DC-MDSs). DCL and DC-MDS can be considered as an in vivo model of leukemogenesis, and even if the pathogenetic mechanisms remain speculative, a genetic predisposition of donor progenitor cells, an altered host microenvironment, and the impairment of immune surveillance are considered the main causes. Case Presentation: We report a case of DC-MDS diagnosed 5 years after an allo-SCT from a matched related donor (patient’s sister) in a patient with Philadelphia chromosome-positive B-cell acute lymphoblastic leukemia (Ph+ B-ALL). The sex-mismatch allowed us to identify the donor cell origin. At the onset, the DC-MDS was characterized by chromosome seven monosomy and NRAS, RUNX1, and BCOR mutations. Because of a familiar history of colorectal neoplasia and the variant allele frequency (VAF) of NRAS mutation at the onset, this mutation was searched on germline DNA in both the donor and the recipient, but the result was negative. Moreover, after transplant (+4 months), the patient developed severe and long-lasting chronic graft-versus-host disease (cGVHD), requiring multiple lines of treatments. Because of the severe immunosuppression, recurrent infections occurred and, lately, the patient died due to septic shock. Conclusion: This case report highlights the need, whenever possible, to evaluate the donor origin of the posttransplant myelodysplasia and acute leukemias. The potential key role of the impaired immune surveillance and of long-lasting immunosuppression appears to be emerging in the development of this case of DC-MDS. Finally, this case reminds the importance to investigate the familiar genetic predisposition in donors with a familiar history of neoplasia

CT-290: Clinical Frailty Scale as a Novel Tool to Evaluate Patients’ Eligibility for Allogeneic Stem Cell Transplant: A Single-Center Experience on 234 Patients >50 Years Old

Context Clinical frailty scale (CFS) is a scale ranging from 1 (very fit) to 9 (terminally ill) for increasing degrees of frailty extensively used in several geriatric contexts. Currently, no study on CFS is available in an allo-HCT setting. Objective To evaluate the prognostic value of CFS on OS and NRM in allo-HCT. Patients and Methods Overall, 234 consecutive patients aged >50 y were transplanted at our center from 2006 to 2020. Median follow-up: 4.03 y (95%CI: 3.54–5.90). CFS was retrospectively calculated by an external physician blind to transplant outcome. Results Cohort characteristics were the following: median age 59 y (range: 50–73), males 147 (63%), AML (44.4%). DRI was high/very-high in 36.8% of cases. Matched related donor was used in 41.5%, unrelated in 46.2%, alternative in 12.3% of cases. Overall, 170 patients (72.6%) received a reduced-intensity conditioning regimen. For the evaluation of patients’ fitness at transplant, the following scores were applied: Karnofsky performance status (≥90 in 91.5%), HCT-CI (≥3 in 43.2%), FIL score (unfit/frail in 6.8%) and CFS (very fit [score 1] in 6.8%, fit [score 2] in 51.3%; managing well [score 3] in 29.9%, and frail [>3] in 12.0%). An increasing CFS score was associated with a higher proportion of FIL frailty and a lower Karnofsky performance status. No significant differences were observed in terms of comorbidities. At last follow-up, 149 (63.7%) patients had died (NRM 41.6%, relapse 58.4%). CFS was strongly associated with OS (2-y-OS of 85.6%, 63.7%, 25.8%, and 7.1% for patients with score 1, 2, 3, and >3, respectively; p<0.0001) and NRM (2-y-NRM of 0%, 15.4%, 33.7%, and 39.2%; p=0.0003). By multivariate analysis, CFS had independent negative prognostic value on OS (HR: 1.87, 95%CI: 1.58–2.22, p<0.001) and NRM (HR: 1.73, 95%CI: 1.30–2.32, p<0.001). As evaluated by the likelihood ratio test and C-statistics, CFS showed a strong predictive value (65.47 and 30.75; 0.695 [SE 0.019] and 0.708 [SE 0.031], for OS and NRM, respectively). Conclusions CFS appears a simple and highly effective tool for transplant outcome prediction among oncohematological patients aged >50 y. These results might suggest the use of this score for improving patient selection