Jarmo Hietala

Purpose: Rhythmic regulation of human neurotransmission systems, particularly the mu-opioid receptor (MOR) and dopamine D2 receptor (D2R) signaling, remains poorly understood. Although prior studies indicate possible diurnal fluctuations in D2R signaling, potential existence of diurnal rhythms in MOR signaling has yet to be investigated. Furthermore, whether and how seasonal factors may override or interact with diurnal rhythms in either system remains unexplored. Decoding these temporal dynamics and their possible links to behavioral traits, such as anxiety, may improve mood regulation models and inspire rhythm-tailored interventions. Methods: Based on a historical PET database of healthy humans scanned with [ ¹¹ C]carfentanil (n = 188) and [ ¹¹ C]raclopride (n = 184), we investigated the diurnal patterns of MOR and D2R availability in the brain, using time-of-day (TOD) of scanning as predictor. Furthermore, we examined whether the TOD differences in receptor availability were modulated by seasonal differences in the daylength (D2R and MOR) and trait-anxiety (MOR). Results: The data revealed increased MOR and decreased D2R availability in the afternoon compared to the morning scans. Interaction with the seasonal effect was, however, observed only for MOR availability, spanning brain areas including anterior cingulate, dorsomedial and dorsolateral prefrontal cortex, insula and striatum. Besides, the diurnal variation of MOR availability in these regions was also sensitive to trait-anxiety levels. Conclusions: The current results reveal the diurnal patterns in opioidergic and dopaminergic neurotransmission with an opposing trajectory. Furthermore, the data highlight a unique role of the MOR system, mediating both types of rhythmic regulations, as well as behavioral traits.

Background: Major depressive disorder (MDD) is clinically heterogeneous, hindering identification of reproducible biomarkers. Using a semi-supervised machine learning approach, HYDRA, we previously identified two neuroanatomical dimensions from structural MRI in medication-free MDD from COORDINATE-MDD consortium. These dimensions (D1, D2) showed differential responses to selective serotonin reuptake inhibitor (SSRI) antidepressants and placebo. External replication in UK Biobank linked D2, characterized by widespread subtle neuroanatomical reductions, to an immuno-metabolic profile. Here, we examined whether these dimensions are detectable early in the course of illness. Methods: We applied the pre-trained model to structural MRI data from the multisite PRONIA cohort, comprising individuals with recent-onset depression (ROD; n = 377; mean age 25.8 years, SD 6.0; 51.3% female) and healthy controls (n = 267; mean age 25.5 years, SD 6.4; 61.0% female). Participants were assigned to clusters (C1, C2) corresponding to the previously identified dimensions (D1, D2). Clusters were compared on clinical symptom profiles, peripheral inflammatory markers, and in a subset (n = 107), proteomic ageing indices. Results: Two neuroanatomical clusters were identified in PRONIA. C1 (n = 265) showed higher negative symptom severity and elevated interleukin-2 levels. C2 (n = 140) was associated with higher residual proteomic age. Overall depressive symptom severity did not differ significantly between clusters. Conclusions: Neuroanatomical dimensions of MDD are reproducible and detectable at illness onset. Associations with negative symptom severity, inflammatory signalling, and proteomic ageing suggest these dimensions capture biologically meaningful heterogeneity early in depression. These findings support a biologically informed framework for stratified treatment approaches in MDD.

Background: A well-established connection exists between psychoses and depression, with one presentation being depressive symptoms before the onset of psychosis. However, the predictive power of preceding affective symptoms is reported to be low, raising the question whether they could reflect typical development associated with high genetic risk for schizophrenia. Thus, we examined whether PRSscz is associated with depressive symptoms from adolescence to middle age in those who did not convert to a non-affective psychosis. Methods: We used the population-based Young Finns Study (n = 2291). Depressive symptoms were measured with the Beck Depression Inventory-II and its modified version (suitable for non-clinical symptoms) between ages 15 and 56. Covariates included age, sex, childhood family environment, and adulthood education and income. The Care Register for Health Care was used to exclude participants with non-affective psychoses until middle age. Results: High PRSscz was associated with higher performance difficulties from adolescence to early adulthood and higher depressive cognitions when approaching middle age. These associations were sustained in the fully adjusted models. PRSscz did not show consistent associations with the total amount of depressive symptoms or somatic/affective symptoms. Conclusions: First, PRSscz appears to explain age‑specific fluctuations in depressive symptoms. Second, PRSscz may not predict the full symptom profile of major depression (i.e., it was not associated with affective/somatic symptoms). Third, high PRSscz explains depressive symptoms during periods typical for prodromal syndromes, even among those who do not develop psychosis. Thus, depressive symptoms in adolescence may represent a developmentally typical pattern associated with high PRSscz.

Group Schema Therapy is an effective option for the treatment of Borderline Personality Disorder but many still fail to benefit. Video Facilitation is explored in our study as an addition to develop this treatment to better fit the needs of the patients. We carried out a pilot study in a Finnish naturalistic sample of eight borderline patients using standard Group Schema Therapy complemented with the Video Facilitation method (previously named VideoTalk). Mixed method approach was used in data gathering and analysis: quantitative data on schemas, schema modes, and psychiatric symptoms were gathered at baseline and post-intervention. Also, there was a semi-structured interview at post-intervention. Therapy method was safe and well tolerated. Schema mode activity transformed towards a more healthy profile and borderline symptoms decreased. During post-intervention interviews use of video was found to enable bringing more emotionally intensive material into the group. Group sessions were perceived as highly important. Changes in self-perception and behavioural skills were reported frequently. Video Facilitation format was suitable and showed promise in intensifying and augmenting the therapy process. Further research is needed to make video-assisted work methods evidence-based therapy.

Symptom diversity in psychoses complicates the search for biological markers. Using Positive and Negative Symptom Scale data from 362 recent-onset patients in the multicenter PRONIA study, we identified four subgroups with dominant symptom patterns: motor/cognitive, positive, social withdrawal, and affective. Subgroups were compared against each other and to 338 healthy controls across neurocognition, brain imaging, and genetic risk. Patient subgroups shared a profile of impaired processing speed and altered functional connectivity, with increased coupling in sensorimotor networks and reduced connectivity within and between default-mode, salience, and control networks. Variations in modality-specific neurobiological underpinnings differentiated subgroups, with fronto-temporal gray-matter loss characterizing the motor/cognitive and positive subgroups, and elevated genetic risk best separating the positive subgroup from the rest. The motor/cognitive group showed the most severe alterations across modalities, reaching the highest multimodal separability from controls (Balanced Accuracy=82.1%, sensitivity=74.9%, specificity=89.3%). Our findings support a framework of shared biological dysfunction with modality-selective vulnerabilities shaping symptom heterogeneity in early-stage psychotic disorders.

Understanding the neurobiological underpinnings of weight gain could reduce excess mortality and improve long-term trajectories of psychiatric disorders. Using brain scans from healthy individuals ( n = 1,504), we trained a model to predict body mass index (BMI) and applied it to individuals with schizophrenia ( n = 146), clinical high-risk states for psychosis ( n = 213) and recent-onset depression (ROD, n = 200). We computed BMIgap (BMI _predicted − BMI _measured ), interrogated its brain-level overlaps with schizophrenia and explored whether BMIgap predicted weight gain at the 1-year and 2-year follow-ups. Schizophrenia (BMIgap = 1.05 kg m ^{− 2} ) and clinical high-risk individuals (BMIgap = 0.51 kg m ^{− 2} ) showed increased BMIgap and individuals with ROD (BMIgap = −0.82 kg m ^{− 2} ) showed decreased BMIgap. Shared brain patterns of BMI and schizophrenia were linked to illness duration, disease onset and hospitalization frequency. Higher BMIgap predicted future weight gain, particularly in younger individuals with ROD, and at 2-year follow-up. Here we show that BMIgap can serve as a potential brain-derived measure to stratify at-risk individuals and deliver tailored interventions for better metabolic risk control.

BACKGROUND: In Parkinson’s disease (PD), the degeneration of nigrostriatal dopaminergic neurons leads to motor symptoms. Positron emission tomography (PET) using radioligand [ ¹⁸ F]fluorodopa detects reduced striatal dopamine synthesis capacity in PD patients. Demographic factors such as sex and BMI are also associated with dopamine synthesis capacity. The combined contribution of demographic and clinical effects however remains elusive. It also remains unresolved how the dopamine synthesis capacity is correlated between striatal subregions and how the dopamine synthesis capacity and dopamine receptor function across striatal regions are associated with each other in PD patients and healthy controls. MATERIAL, AIMS, AND METHODS: For this retrospective register-based study, we used baseline [ ¹⁸ F]fluorodopa PET data acquired at the Turku PET Centre between the years 1988-2016 with three different scanners (Ecat 931, GE Advance, HRRT). The data included scans of 350 adult human subjects, including 132 healthy controls (65 males and 67 females), and 218 PD patients (134 males and 84 females). The primary aim was to simultaneously investigate the effects of PD, age, sex and BMI on regional dopamine synthesis capacity (influx rate constant Ki ^ref quantified with Patlak) using Bayesian linear regression. Secondary aims were to assess interregional correlations of dopamine synthesis capacity, and the association between regional presynaptic dopamine synthesis and postsynaptic dopamine type 2 receptor (D ₂ R) availability in subjects who also had a proximal [ ¹¹ C]raclopride PET scan. RESULTS: We found modest support for age-dependent decline in dopamine synthesis capacity, increased capacity for higher BMIs, and for higher capacity in females versus males. These effects were smaller than the effect of PD status. Dopamine synthesis capacity across regions was correlated in both patients and controls. Support for positive correlation between the synthesis capacity and the D ₂ R was observed in caudate nucleus. CONCLUSIONS: PD and demographic effects are independently associated with the striatal dopamine synthesis capacity. The capacity is reduced by PD, decreased through age (particularly after the age of around 50), higher in females versus males, and weakly increased in higher BMIs. Synthesis capacity is correlated between the striatal and thalamic regions in both PD patients and controls. The dopamine synthesis capacity was positively correlated with the D ₂ R availability in caudate. Scanner affects the estimates of dopamine synthesis capacity measured with [ ¹⁸ F]fluorodopa PET, and it is preferrable to adjust for such variation in the data.

Neurotransmitter receptors guide the propagation of signals between brain regions. Mapping receptor distributions in the brain is therefore necessary for understanding how neurotransmitter systems mediate the link between brain structure and function. Normative receptor density can be estimated using group averages from Positron Emission Tomography (PET) imaging. However, the generalizability and reliability of group-average receptor maps depends on the inter-individual variability of receptor density, which is currently unknown. Here we collect group standard deviation brain maps of PET-estimated protein abundance for 12 different neurotransmitter receptors and transporters across 7 neurotransmitter systems, including dopamine, serotonin, acetylcholine, glutamate, GABA, cannabinoid, and opioid. We illustrate how cortical and subcortical inter-individual variability of receptor and transporter density varies across brain regions and across neurotransmitter systems. We complement inter-individual variability with inter-regional variability, and show that receptors that vary more across brain regions than across individuals also demonstrate greater out-of-sample spatial consistency. Altogether, this work quantifies how receptor systems vary in healthy individuals, and provides a means of assessing the generalizability of PET-derived receptor density quantification.