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Alzheimer’s disease (AD), the most common form of dementia worldwide, is a mixed proteinopathy (β-amyloid, tau and other proteins). Classically defined as a clinicopathological entity, AD is a heterogeneous, multifactorial disorder with various pathobiological subtypes showing different forms of cognitive presentation, currently referred to as the Alzheimer spectrum or continuum. Its morphological hallmarks are extracellular β-amyloid (amyloid plaques) and intraneuronal tau aggregates forming neurofibrillary tangles and neurites, vascular amyloid deposits (cerebral amyloid angiopathy), synapse and neuronal loss as well as neuroinflammation and reactive astrogliosis, leading to cerebral atrophy and progressive mental/cognitive impairment (dementia). In addition to “classical” AD, several subtypes with characteristic regional patterns of tau pathology have been segregated that are characterized by distinct clinical features, differences in age, sex distribution, disease duration, cognitive status, APOE genotype, and biomarker levels. In addition to four major subtypes based on the distribution of tau pathology and brain atrophy (typical, limbic predominant, hippocampal sparing, and minimal atrophy), several other clinical variants (non-amnestic, corticobasal, behavioral/dysexecutive, posterior cortical variants, etc.) have been identified. These heterogeneous AD variants are characterized by different patterns of key neuronal network destructions, in particular the default-mode network that is responsible for cognitive decline. Other frequent age-related co-pathologies, e.g., cerebrovascular lesions, Lewy and TDP-43 pathologies, hippocampal sclerosis, or argyrophilic grain disease, essentially influence the clinical picture and course of AD, and can challenge our understanding of this disorder including the threshold and causal relevance of each individual pathology. Unravelling the clinico-morphological heterogeneity among the AD spectrum entities is important for better elucidation of the pathogenic mechanisms affecting the aging brain that may enable a broader diagnostic coverage of AD as a basis for implementing precision medicine approaches and for developing preventive and ultimately disease-modifying therapies for this devastating disorder.

Patients with preeclampsia display a spectrum of onset time and severity of clinical presentation, yet the underlying molecular bases for the early-onset and late-onset clinical subtypes are not known. Although several transcriptome studies have been done on placentae from PE patients, only a small number of differentially expressed genes have been identified due to very small sample sizes and no distinguishing of clinical subtypes. We carried out RNA-seq on 65 high-quality placenta samples, including 33 from 30 patients and 32 from 30 control subjects, to search for dysregulated genes and the molecular network and pathways they are involved in. We identified two functionally distinct sets of dysregulated genes in the two major subtypes: 2,977 differentially expressed genes in early-onset severe preeclampsia, which are enriched with metabolism-related pathways, notably transporter functions; and 375 differentially expressed genes in late-onset severe preeclampsia, which are enriched with immune-related pathways. We also identified some key transcription factors, which may drive the widespread gene dysregulation in both early-onset and late-onset patients. These results suggest that early-onset and late-onset severe preeclampsia have different molecular mechanisms, whereas the late-onset mild preeclampsia may have no placenta-specific causal factors. A few regulators may be the key drivers of the dysregulated molecular pathways.

Operational definitions of cognitive impairment have varied widely in diagnosing mild cognitive impairment (MCI). Identifying clinical subtypes of MCI has further challenged diagnostic approaches because varying the components of the objective cognitive assessment can significantly impact diagnosis. Therefore, the authors investigated the applicability of diagnostic criteria for clinical subtypes of MCI in a naturalistic research sample of community elders and quantified the variability in diagnostic outcomes that results from modifying the neuropsychological definition of objective cognitive impairment. Cross-sectional and longitudinal study. San Diego, CA, Veterans Administration Hospital. Ninety nondemented, neurologically normal, community-dwelling older adults were initially assessed and 73 were seen for follow-up approximately 17 months later. Participants were classified via consensus diagnosis as either normally aging or having MCI via each of the five diagnostic strategies, which varied the cutoff for objective impairment and the number of neuropsychological tests considered in the diagnostic process. A range of differences in the percentages identified as MCI versus cognitively normal were demonstrated, ranging from 10–74%, depending on the classification criteria used. A substantial minority of individuals demonstrated diagnostic instability over time and across diagnostic approaches. The single domain nonamnestic subtype diagnosis was particularly unstable (e.g., prone to reclassification as normal at follow up). Our findings provide empirical support for a neuropsychologically derived operational definition of clinical subtypes of MCI and point to the importance of using comprehensive neuropsychological assessments. Diagnoses, particularly involving nonamnestic MCI, were variable over time. The applicability and utility of this particular MCI subtype warrants further investigation.

Bipolar disorder (BD) is an overarching diagnostic class defined by the presence of at least one prior manic episode (BD I) or both a prior hypomanic episode and a prior depressive episode (BD II). Traditionally, BD II has been conceptualized as a less severe presentation of BD I, however, extant literature to investigate this claim has been mixed. We apply genomic structural equation modeling (Genomic SEM) to investigate divergent genetic pathways across BD's two major subtypes using the most recent GWAS summary statistics from the PGC. We begin by identifying divergences in genetic correlations across 98 external traits using a Bonferroni-corrected threshold. We also use a theoretically informed follow-up model to examine the extent to which the genetic variance in each subtype is explained by schizophrenia and major depression. Lastly, transcriptome-wide SEM (T-SEM) was used to identify neuronal gene expression patterns associated with BD subtypes. BD II was characterized by significantly larger genetic overlap across non-psychiatric medical and internalizing traits (e.g. heart disease, neuroticism, insomnia), while stronger associations for BD I were absent. Consistent with these findings, follow-up modeling revealed a substantial major depression component for BD II. T-SEM results revealed 35 unique genes associated with shared risk across BD subtypes. Divergent patterns of genetic relationships across external traits provide support for the distinction of the bipolar subtypes. However, our results also challenge the illness severity conceptualization of BD given stronger genetic overlap across BD II and a range of clinically relevant traits and disorders.

Purpose This study evaluated whether patients with de novo metastatic breast cancer (MBC) have superior outcomes compared to those with recurrent MBC in a contemporary treatment era and examined factors related to outcome differentials. Methods Using an institutional database, we examined patient and tumor characteristics, treatment response, and outcome among 232 patients with de novo and 612 patients with recurrent MBC diagnosed between 2011 and 2017. Results De novo MBC had 9-month (m) longer overall survival (OS) than recurrent MBC (36.4 vs 27.4 m, p  < 0.001). Contributions to this difference included nearly twofold more HER2-positive (29.3% vs 15.2%) and significantly fewer triple-negative breast cancers (20.3% vs 32.4%, both p  < 0.001) in de novo compared with recurrent MBC cohorts. Stratified by clinical subtype, progression-free survival (PFS) on first-line therapy was significantly longer in de novo MBC in all but the triple-negative subtype, 25.5 vs 11.6 m ( p  < 0.001) among 390 patients with hormone receptor-positive, HER2-negative, 11.4 vs 5.4 m ( p  = 0.002) among 142 patients with HER2-positive, and 4.0 vs 3.0 m ( p  = 0.121) among 162 with triple-negative MBC. In multivariable analysis, de novo status remained independently associated with improved OS (hazard ratio 0.63, 95% CI 0.49–0.80), regardless of subtype and other features. Conclusion Patients with de novo MBC have better outcomes than those with recurrent MBC. Differences in clinical subtype and response to therapy in the metastatic setting contribute to, but do not fully explain, this difference. Longer PFS to first-line therapy in de novo MBC suggests biologic differences compared to recurrent MBC, which may be intrinsic or due to acquired resistance from treatment for prior localized breast cancer in recurrent disease.

Adult T‐cell leukemia/lymphoma (ATL) is a mature T‐cell neoplasm and is classified into four subtypes (acute, lymphoma, chronic, and smoldering) according to the Shimoyama classification, established in 1991 through several nationwide surveys based on the clinical diversity of patients diagnosed in 1983‐1987 in Japan. Thereafter, no such studies have been conducted. Recently, we conducted a nationwide hospital survey using the method of the 1980s studies, collected baseline data on 996 ATL patients diagnosed in 2010‐2011 from 126 hospitals, and reported their unique epidemiological characteristics. Here, we report the follow‐up results of registered ATL patients with the goal of evaluating current prognoses and treatment modalities as of 2016‐2017. Of 770 evaluable patients, 391 (50.8%) had acute‐type, 192 (24.9%) had lymphoma‐type, 106 (13.8%) had chronic‐type, and 81 (10.5%) had smoldering‐type ATL. The initial therapy regimens used for acute/lymphoma‐type ATL were vincristine, cyclophosphamide, doxorubicin and prednisone, followed by doxorubicin, ranimustine, and prednisone and then by vindesine, etoposide, carboplatin, and prednisone (VCAP‐AMP‐VECP)‐like in 38.5/41.7% and cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP)‐like in 14.6/13.7% of patients. Allogeneic hematopoietic stem cell transplantation was used to treat 15.9/10.4% of acute/lymphoma‐type ATL patients. The 4‐year survival rates (the median survival time, days) for acute‐, lymphoma‐, unfavorable chronic‐, favorable chronic‐, and smoldering‐type ATL were 16.8% (252), 19.6% (305), 26.6% (572), 62.1% (1937), and 59.8% (1851), respectively. The 4‐year survival rates for acute‐ and lymphoma‐type ATL improved compared with those reported in 1991, but those for chronic‐ and smoldering‐type ATL were not. Further efforts are warranted to develop more efficient therapeutic strategies to improve the prognosis of ATL in Japan. The survival curve shows that the prognoses of patients with acute and lymphoma‐type ATL in Japan have improved modestly, but those of patients with chronic and smoldering‐type ATL have not improved.

Objective: Insights to underlying neural mechanisms in ADHD have emerged from neuroimaging research; however, the neural mechanisms that distinguish ADHD subtypes remain inconclusive. Method: We reviewed nineteen studies integrating magnetic resonance imaging (structural, diffusion, fMRI) findings into a framework exploring pathophysiological mechanisms underlying the combined (ADHD-C) and predominantly inattentive (ADHD-I) ADHD subtypes. Results: Despite equivocal structural MRI results, findings from fMRI and DTI imaging modalities consistently implicate disrupted connectivity in regions and tracts involving frontal striatal thalamic in ADHD-C and frontoparietal neural networks in ADHD-I. Alterations of the default mode, cerebellum and motor networks in ADHD-C and cingulo-frontoparietal attention and visual networks in ADHD-I highlight network organization differences between subtypes. Conclusion: Growing evidence from neuroimaging studies highlight neurobiological differences between ADHD clinical subtypes, particularly from a network perspective. Understanding brain network organization and connectivity may help us to better conceptualize the ADHD types and their symptom variability.

Background While xanthine oxidase inhibitors target uric acid production, renal urate underexcretion is the predominant subtypes in gout. This study was to compare treatment response to the XOI febuxostat in a gout cohort according to clinical subtypes of hyperuricemia. Methods A prospective cohort study was conducted to compare the efficacy and safety of febuxostat (initially 20 mg daily, escalating to 40 mg daily if not at target) in 644 gout patients with the three major clinical subtypes for 12 weeks. Hyperuricemia was defined as the renal overload subtype, the renal underexcretion subtype, or the combined subtype based on UUE > or ≤ 600 mg/d/1.73 m 2 and FE UA  < or ≥ 5.5%. The primary endpoint was the rate of achieving serum urate (SU) < 6 mg/dL at week 12. Results Fewer participants with combined subtype achieved the SU target, 45.5% compared with 64.8% with overload subtype ( P  = 0.007), and 56.6% with underexcretion subtype ( P  = 0.022). More participants with combined subtype (82%) had febuxostat escalated to 40 mg than those with overload (62%, P  = 0.001) or underexcretion subtype (68%, P  = 0.001). In all participants, combined subtype hyperuricemia (OR = 0.64, 95%CI 0.41–0.99, P  = 0.048) and baseline SU (OR = 0.74, 95%CI 0.62–0.89, P  = 0.001) were independently associated with lower rates of achieving SU target. Conclusions People with combined subtype have a lower response to febuxostat, compared to those with either overload or underexcretion subtype. Assessment of hyperuricemia subtype may provide useful clinical data in predicting febuxostat response. Key Message • Combined subtype of hyperuricemia had lower urate-lowering response to febuxostat compared with other subtypes. • Typing as combined subtype and baseline serum urate were independent risk factors for targeting. • Assessment of hyperuricemia clinical subtype may provide useful data in predicting febuxostat response.

Background: Molecular subtyping of breast cancer has provided a new perspective on the pathogenesis of the disease and a foundation for building a clinical classification for this heterogeneous disease. The initial classification categorizing breast cancers into five groups, luminal A, luminal B, ERBB2-overexpressing, basal-like and normal-like, was later supplemented by an additional group, claudin-low tumors. However, the claudin-low group has been more difficult to align with clinically used immunohistochemical categories. The identity of this group among clinical cases remains ill defined. Methods: The METABRIC cohort comprising more than 1700 breast cancers and providing information for classifying them in both clinical groups and the genomic PAM50/claudin-low groups was analyzed to derive relationships and clarify potential pathogenic ramifications. Comparisons of the claudin-low cases bearing different clinical group classifications and of the respective cases with the same clinical non-claudin-low classifications were performed. Results: ER-negative/HER2-negative breast cancers are predominantly (88.4%) basal-like and claudin low. Conversely, most basal-like cancers (83.6%) are ER negative/HER2 negative. However, claudin-low breast cancers are only in 68.4% of cases ER negative/HER2 negative and the other clinical phenotypes, mostly ER positive/HER2 negative/low proliferation, are also represented in more than 30% of claudin-low cancers. These claudin-low non-ER-negative/HER2-negative breast cancers differ from claudin-low ER-negative/HER2-negative cases in grade, prevalence of integrative clusters, and prevalence of common mutations and common amplifications. Differences also exist between the two groups classified clinically as ER negative/HER2 negative, that are genomically basal-like or claudin-low, including in menopause status, grade, histology, prevalence of high tumor mutation burden, distribution of integrative clusters, prevalence of TP53 mutations and of amplifications in the MYC and MCL1 loci. Furthermore, distinct characteristics are observed between the luminal A and claudin-low groups within the clinical ER-positive/HER2-negative/low proliferation group. Conclusion: Within genomically claudin-low breast cancers, the ER-negative/HER2-negative group is distinct from the group with either ER or HER2 positivity. Conversely, within clinical phenotypes, claudin-low and non-claudin-low breast cancers differ in clinical characteristics and molecular attributes.

Obsessive-compulsive disorder (OCD) is characterized by recurrent intrusive thoughts, urges, or images (obsessions) and repetitive physical or mental behaviors (compulsions). Previous factor analytic and clustering studies suggest the presence of three or four subtypes of OCD symptoms. However, these studies have relied on predefined symptom checklists, which are limited in breadth and may be biased toward researchers' previous conceptualizations of OCD.BACKGROUNDObsessive-compulsive disorder (OCD) is characterized by recurrent intrusive thoughts, urges, or images (obsessions) and repetitive physical or mental behaviors (compulsions). Previous factor analytic and clustering studies suggest the presence of three or four subtypes of OCD symptoms. However, these studies have relied on predefined symptom checklists, which are limited in breadth and may be biased toward researchers' previous conceptualizations of OCD.In this study, we examine a large data set of freely reported obsession symptoms obtained from an OCD mobile app as an alternative to uncovering potential OCD subtypes. From this, we examine data-driven clusters of obsessions based on their latent semantic relationships in the English language using word embeddings.OBJECTIVEIn this study, we examine a large data set of freely reported obsession symptoms obtained from an OCD mobile app as an alternative to uncovering potential OCD subtypes. From this, we examine data-driven clusters of obsessions based on their latent semantic relationships in the English language using word embeddings.We extracted free-text entry words describing obsessions in a large sample of users of a mobile app, NOCD. Semantic vector space modeling was applied using the Global Vectors for Word Representation algorithm. A domain-specific extension, Mittens, was also applied to enhance the corpus with OCD-specific words. The resulting representations provided linear substructures of the word vector in a 100-dimensional space. We applied principal component analysis to the 100-dimensional vector representation of the most frequent words, followed by k-means clustering to obtain clusters of related words.METHODSWe extracted free-text entry words describing obsessions in a large sample of users of a mobile app, NOCD. Semantic vector space modeling was applied using the Global Vectors for Word Representation algorithm. A domain-specific extension, Mittens, was also applied to enhance the corpus with OCD-specific words. The resulting representations provided linear substructures of the word vector in a 100-dimensional space. We applied principal component analysis to the 100-dimensional vector representation of the most frequent words, followed by k-means clustering to obtain clusters of related words.We obtained 7001 unique words representing obsessions from 25,369 individuals. Heuristics for determining the optimal number of clusters pointed to a three-cluster solution for grouping subtypes of OCD. The first had themes relating to relationship and just-right; the second had themes relating to doubt and checking; and the third had themes relating to contamination, somatic, physical harm, and sexual harm. All three clusters showed close semantic relationships with each other in the central area of convergence, with themes relating to harm. An equal-sized split-sample analysis across individuals and a split-sample analysis over time both showed overall stable cluster solutions. Words in the third cluster were the most frequently occurring words, followed by words in the first cluster.RESULTSWe obtained 7001 unique words representing obsessions from 25,369 individuals. Heuristics for determining the optimal number of clusters pointed to a three-cluster solution for grouping subtypes of OCD. The first had themes relating to relationship and just-right; the second had themes relating to doubt and checking; and the third had themes relating to contamination, somatic, physical harm, and sexual harm. All three clusters showed close semantic relationships with each other in the central area of convergence, with themes relating to harm. An equal-sized split-sample analysis across individuals and a split-sample analysis over time both showed overall stable cluster solutions. Words in the third cluster were the most frequently occurring words, followed by words in the first cluster.The clustering of naturally acquired obsessional words resulted in three major groupings of semantic themes, which partially overlapped with predefined checklists from previous studies. Furthermore, the closeness of the overall embedded relationships across clusters and their central convergence on harm suggests that, at least at the level of self-reported obsessional thoughts, most obsessions have close semantic relationships. Harm to self or others may be an underlying organizing theme across many obsessions. Notably, relationship-themed words, not previously included in factor-analytic studies, clustered with just-right words. These novel insights have potential implications for understanding how an apparent multitude of obsessional symptoms are connected by underlying themes. This observation could aid exposure-based treatment approaches and could be used as a conceptual framework for future research.CONCLUSIONSThe clustering of naturally acquired obsessional words resulted in three major groupings of semantic themes, which partially overlapped with predefined checklists from previous studies. Furthermore, the closeness of the overall embedded relationships across clusters and their central convergence on harm suggests that, at least at the level of self-reported obsessional thoughts, most obsessions have close semantic relationships. Harm to self or others may be an underlying organizing theme across many obsessions. Notably, relationship-themed words, not previously included in factor-analytic studies, clustered with just-right words. These novel insights have potential implications for understanding how an apparent multitude of obsessional symptoms are connected by underlying themes. This observation could aid exposure-based treatment approaches and could be used as a conceptual framework for future research.