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. 2026 Jan 15;62:46–56. doi: 10.1016/j.jdsr.2026.01.001

Beyond the diagnosis: Unraveling DSPP genotype-phenotype correlations in dentin dysplasia and dentinogenesis imperfecta

Angkana Boonyakanog a, Kanokrat Sriwangyang a, Thamasorn Eamtanaporn a,b, Annop Krasaesin a,c, Kausar Sadia Fakhruddin d,e, Soranun Chantarangsu f, Sung-Dae Cho g, Hamid A Rokny h,i, Thantrira Porntaveetus a,j,⁎
PMCID: PMC12830278  PMID: 41583696

Abstract

The DSPP gene regulates dentin mineralisation, and its pathogenic variants cause a spectrum of defects ranging from dentin dysplasia (DD-II) to dentinogenesis imperfecta (DGI-II/III). Clinical variability often confounds diagnosis. This systematic review of 48 publications (70 variants, 99 records) delineates quantitative genotype–phenotype correlations. Results revealed distinct molecular clustering: Exon 5 harboured 61 % of variants, predominantly frameshifts disrupting the repetitive dentin phosphoprotein (DPP) domain. In contrast, upstream regions (exons 2–4) contained mixed variant types affecting the signal peptide and dentin sialoprotein (DSP). Statistical analysis established a definitive severity gradient. Exon 5 frameshifts were significantly associated with the milder DD-II, characterised by thistle-shaped pulps and clinically normal permanent dentition. Conversely, upstream signal peptide, splice site, and missense variants (exons 2–3) were linked to the severe DGI-III, manifesting as ‘shell teeth’, rapid attrition, and pulp exposure requiring complex prosthodontic intervention. DGI-II displayed no specific genomic clustering, representing an intermediate phenotype. These findings provide complementary insights to historical classifications, highlighting a continuous spectrum of DSPP disorders where upstream defects cause severe failure, while downstream defects result in attenuated localised anomalies. Consequently, integrating DSPP genotyping into diagnostic workflows is essential to predict disease progression, refine molecular taxonomy beyond the Shields system, and guide personalised rehabilitation.

Keywords: DSPP, Dentinogenesis imperfecta, Dentin dysplasia, DFNA39, Hereditary dentin disorder, Healthcare access

1. Introduction

Hereditary dentin disorders constitute a group of conditions resulting from genetic variants that affect the development of tooth dentin, the mineralised connective tissue underlying the enamel and surrounding the pulp complex [1], [2]. In 1973, Shields et al. proposed a classification system dividing dentin dysplasia (DD) into two subtypes and dentinogenesis imperfecta (DGI) into three categories [3]. Clinically, DD-I (OMIM *125400) is a rare hereditary dental anomaly characterised by normal crown morphology in both dentitions, accompanied by abnormal root formation and early tooth loss [4]. DD-II (OMIM *125420) presents distinct features: primary teeth display amber discolouration resembling DGI, while permanent crowns appear normal, though radiographs reveal thistle-shaped pulp chambers and pulp stones [5]. Within the DGI categories, DGI-I (OMIM *166200) is associated with osteogenesis imperfecta (OI) and systemic bone disease. DGI-II (OMIM *125490) exhibits a phenotype similar to DGI-I including amber discolouration, bulbous crowns, and pulp obliteration—but occurs in the absence of bone fragility [6], [7]. Finally, DGI-III (OMIM *125500), originally described in the Brandywine isolate [8], is distinguished by ‘shell teeth’ with extremely large pulp chambers that subsequently obliterate [9]. Advances in molecular genetics have challenged these historical classifications. It is now established that DD-I is genetically heterogeneous (associated with VPS4B, SSUH2, and SMOC2), and DGI-I is caused by collagen defects (COL1A1, COL1A2) [10], [11]. However, DD-II, DGI-II, and DGI-III have been identified as allelic disorders caused by variants within the distinct dentin sialophosphoprotein (DSPP) gene (OMIM *125485). Despite overlapping phenotypes, the clinical distinction between these DSPP-associated conditions remains ambiguous. While variant-level characterisation is now possible, a unified synthesis linking specific DSPP genotypes to clinical presentation has not yet been achieved.

Dentinogenesis is a tightly regulated process involving the sequential secretion and mineralisation of dentin matrix proteins by odontoblasts [12], [13], [14]. The DSPP gene, located on chromosome 4q21.3, comprises five exons and four introns [15]. It encodes a precursor protein that is post-translationally cleaved into dentin sialoprotein (DSP), dentin glycoprotein (DGP), and dentin phosphoprotein (DPP), all of which are essential for normal dentinogenesis [16]. Exons 2–4 primarily encode the DSP region, including an N-terminal signal peptide, whereas exon 5 encodes the C-terminal region of DSP, DGP, and DPP. These proteins orchestrate dentin formation: DSP initiates mineralisation [17], DGP likely aids matrix organisation [16], and the aspartic acid-rich DPP promotes hydroxyapatite crystal formation and dentin maturation [18], [19]. Variants affecting these domains can disrupt protein trafficking or mineralisation, resulting in a spectrum of dental defects.

Although molecular advancements have improved the identification of DSPP variants [20], [21], current data remain fragmented across isolated reports. A unified synthesis linking variant class and genomic position to clinical severity is lacking. Therefore, this study systematically reviews published DSPP variants to establish quantitative genotype-phenotype correlations. We aim to [1] catalogue variants and their genomic localisation; [2] analyse associations between variant type, domain, and phenotype, and [3] determine how genomic data can refine the classification and management of hereditary dentin disorders.

2. Materials and methods

This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines. The protocol was submitted on PROSPERO (CRD420251170506) (https://www.crd.york.ac.uk/PROSPERO/view/CRD420251170506). All steps, including database search, screening, data extraction, and synthesis, were conducted in accordance with the PRISMA checklist (Supplementary Table 1).

2.1. Bibliographic search

The systematic literature search was performed across PubMed, Scopus, Embase, and ProQuest databases to identify studies reporting DSPP gene variants associated with hereditary dentin disorders. No search date restrictions were applied; therefore, the identified publications spanned from January 1997 to August 2025, representing the full scope of the available literature at the time of the final search conducted on September 1, 2025.

The search strategy combined both MeSH and free-text terms, including (“dentin dysplasia” OR “dentinogenesis imperfecta” OR “hereditary dentin disorder”) AND (“DSPP” OR “dentin sialophosphoprotein”). Reference lists of relevant studies were manually screened to capture additional eligible records. The search strategy was independently verified by two reviewers (AB, KS) and documented for transparency. All retrieved records were imported into EndNote for duplicate removal.

2.1.1. Eligibility criteria

Inclusion criteria:

  • (1)

    Studies reporting DSPP variants confirmed by DNA sequencing in individuals diagnosed with DD or DGI.

  • (2)

    Reports providing sufficient clinical and/or radiographic characterisation to establish phenotypes.

  • (3)

    Human studies, written in English, and published in peer-reviewed journals.

Exclusion criteria:

  • (1)

    Animal or in vitro studies

  • (2)

    Review articles, conference abstracts, or reports without original genetic data

  • (3)

    Studies reporting DSPP polymorphisms or synonymous variants with no phenotypic description.

2.2. Data extraction and analysis

Data extraction was performed independently by three reviewers (AB, KS, and TE). For each case, the type and genomic location of the DSPP variant were recorded, along with the associated dental phenotype, classified as either DD or DGI. Each publication was treated as an independent source of DSPP variants. Identical variants reported across different studies were counted individually, as they generally represented distinct families and geographic origins. Conversely, when a variant was reported multiple times from the same family, typically within a single publication, it was recorded as a single occurrence. This approach facilitated the assessment of reporting frequency and the identification of recurrent variants and mutational hotspots.

Variants in the DSPP gene (NCBI CCDS 43248.1, NM_014208.3, NP_055023.2) were classified according to three main categories: [1] clinical diagnosis, [2] genomic location, and [3] variant type. All variants were described following the nomenclature standards recommended by the Human Genome Variation Society (HGVS) [22].

Clinical diagnosis was collected in accordance with the original study descriptions and classified as DD-II, DGI-II, DGI-III, DGI, and DD-II/DGI-II. Patients designated as DGI or DD-II/DGI-II were classified separately, because the original publications used the term DGI without specifying whether the diagnosis corresponded to DGI-II or DGI-III. Moreover, in research describing DD-II/DGI-II, the clinical manifestations overlapped, and the phenotypes could not be clearly differentiated, since affected individuals exhibited features characteristic of both conditions. Clinical photographs and radiographs, if provided, were used to confirm the phenotype. Genomic locations were categorised according to the positions of reported variants within the DSPP gene, including exon 2, intron 2, exon 3, intron 3, exon 4, and exon 5. The variants were further classified according to their predicted pathogenic mechanisms, including alterations affecting the signal peptide region, signal peptide cleavage site, splice sites, as well as missense, nonsense, and frameshift variants. The frequency of each variant type within specific gene domains was subsequently summarised to investigate potential genotype–phenotype correlations.

Phenotypic information, such as discolouration, pulp obliteration, root morphology, and the presence of pulp stones, associated with each DSPP variant was extracted and included in the analysis. When the same variant was associated with multiple phenotypic presentations across different reports, all phenotypes were recorded to capture the full phenotypic spectrum. Disagreements were resolved by consensus or adjudication by a fourth reviewer (TP).

2.2.1. Quality and bias assessment

Methodological quality and reporting completeness of each included study were evaluated using an adapted version of the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Case Reports and Case Series [23]. Each study was scored on criteria such as clarity of genetic testing method, phenotype documentation, segregation analysis, and variant interpretation. Studies were categorised as high (≥8/10), moderate (6–7/10), or low quality (≤5/10) (Supplementary Table 2).

2.3. Statistical analysis

Statistical analyses were performed using GraphPad Prism (GraphPad Software, Inc., CA, USA) and IBM SPSS Statistics for Windows (IBM Corp., NY, USA). The chi-square test was employed to compare the prevalence of phenotypic characteristics across clinical diagnosis, genomic regions, and different variant types of DSPP. Statistical significance was assessed using both exact p-values and letter-based group comparisons in figures and tables, with thresholds defined as *p-value ≤ 0.05, **p-value ≤ 0.01, ***p-value ≤ 0.001, and ****p-value ≤ 0.0001.

3. Results

3.1. Spectrum and distribution of pathogenic DSPP Gene variants

A total of 48 publications reporting patients with DD or DGI associated with DSPP variants were included in the analysis (Fig. 1). From these studies, 70 distinct DSPP variants were identified (Fig. 2A, Supplementary Table 3). The genomic distribution of these variants was highly non-uniform. Exon 5, the longest exon encoding the dentin phosphoprotein (DPP) domain, was the predominant mutational hotspot, harbouring 61 % (43/70) of all variants. In contrast, exons 2, 3, and 4, along with introns 2 and 3, collectively accounted for the remaining 39 % of variants, with exon 4 containing the fewest (4 %, 3/70). When categorised by variant type, frameshift variants were the most prevalent, constituting 60 % (42/70) of the total. Splice site variants were the second most common (22 %, 15/70), while missense, nonsense, and signal peptide-related variants (affecting the peptide itself or its cleavage site) were less frequent (4–6 % each). All categories were predicted to be pathogenic and contribute to dentin-related disorders.

Fig. 1.

Fig. 1

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Flow diagram of the study identification and selection process.

Fig. 2.

Fig. 2

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Schematic of DSPP showing the location and frequency of identified pathogenic variants. (A) Pie charts illustrating the proportion of variants across the DSPP gene and the relative frequency of different variant types. (B) Pie charts showing the distribution of variant types within each genomic region (exons 2–5 and introns 2–3).

A striking pattern emerged when variant type was cross-referenced with genomic location (Fig. 2B). All variants within intronic regions (introns 2 and 3) were splice site variants (100 %). Exon 2 variants exclusively affected the signal peptide region (3 signal peptide variants, 3 cleavage site variants). Exon 3 contained a mix of splice site (57 %) and missense (43 %) variants. Exon 4 variants were primarily nonsense (67 %), with one missense change. Most notably, variants in exon 5 were overwhelmingly frameshift variants (98 %, 42/43), with a single nonsense variant. These findings confirm that the molecular pathogenesis of DSPP disorders is heavily influenced by exon-specific architecture.

3.2. Correlating variant location and type with clinical diagnosis

We analysed 99 reported genotype-phenotype records to assess the relationship between DSPP variants and clinical diagnoses (Fig. 3A, B). DGI-II was the most frequently reported diagnosis (47 %, 47/99), followed by DD-II (22 %, 22/99), non-specified DGI (14 %, 14/99), DGI-III (13 %, 13/99), and overlapping DD-II/DGI-II (3 %, 3/99).

Fig. 3.

Fig. 3

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Distribution of DSPP variant reports by associated clinical diagnoses. (A) Bar graph depicting the frequency of reported clinical diagnoses corresponding to variants across different regions of the DSPP gene. (B) Bar graph summarising the total number of reported clinical diagnoses. (C) Table presenting chi-square analysis of the association between clinical diagnoses, variant locations, and variant types within the DSPP gene. Asterisks indicate statistically significant differences, with significance defined as follows: *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001, ****p ≤ 0.0001.

Statistical analysis revealed significant associations between the clinical diagnosis and both the genomic location and variant type for several disorders (Fig. 3C). DD-II was significantly associated with variants in exon 5 and was most frequently caused by frameshift variants (Supplementary Table 4). Conversely, DGI-III was strongly linked to variants in exons 2 and 3 and was notably absent in cases with exon 5 variants. This severe form was primarily driven by missense variants. The non-specified DGI group showed a predominant association with exon 4 and nonsense variants. In contrast, DGI-II and the DD-II/DGI-II overlap group showed no significant correlation with specific genomic locations or variant types, reflecting their intermediate and variable position on the phenotypic spectrum.

3.3. Genotype-phenotype correlations in dental features

A detailed analysis of specific dental phenotypes revealed clear gradients of severity that correlated with the genetic alterations (Table 1, Fig. 4, Fig. 5, Fig. 6). These features were categorised into four major groups: medical history, oral investigations, oral radiographs, and treatments. Features identifiable through both oral examination and radiographs were assigned to a single category for clarity and ease of interpretation.

Table 1.

Chi-square analysis of genotype–phenotype correlations in DSPP-related hereditary dentin disorders.

Phenotypes Diagnoses Locations Variant types
p-value p-value p-value
Medical history
Hearing loss (DFNA39) 0.5856 0.9173 0.9078
Bone fractures 0.9375 0.9172 0.9172
Oral investigations
Clinically normal permanent dentition < 0.0001**** < 0.0001**** < 0.0001****
Opalescent-brown 0.3059 0.1018 0.4594
Yellow-brown 0.2428 0.6782 0.7321
Amber brown 0.3484 0.1104 0.4764
Grayish-blue 0.1068 0.2850 0.3626
Attrition 0.4824 0.7324 0.6082
Severe attrition 0.0015** 0.0108* 0.0108*
Erosion 0.6194 0.0076** 0.1959
Abrasion 0.6194 0.0076** 0.1959
Hypoplastic enamel 0.4668 0.0706 0.2215
Enamel deterioration 0.012* 0.0006*** 0.0152*
Dentin deterioration 0.3015 0.0037** 0.0177*
Dentin exposure 0.6815 0.3611 0.7685
Missing/Extracted teeth 0.2228 0.8161 0.3337
Teeth sensitivity 0.0009*** < 0.0001**** < 0.0001****
Oral radiographs
Cervical constriction 0.0341* 0.9885 0.7479
Bulbous crowns 0.0728 0.1200 0.0760
Shell teeth 0.0003*** 0.0198* 0.0580
Periapical lesions 0.0893 0.1821 0.0747
Pulp exposure 0.0001*** 0.0704 0.0488*
Pulp obliteration 0.0042** 0.5419 0.4345
Complete pulp obliteration < 0.0001**** 0.5333 0.4715
Enlarged pulp cavity 0.0541 0.0350* 0.0252*
Thistle-shaped pulp chamber < 0.0001**** 0.0949 0.0445*
Pulp stones 0.0045** 0.4762 0.6441
Short root 0.2293 0.2044 0.2152
Thin root 0.5503 0.0054** 0.0047**
Root canal obliteration 0.1895 0.7775 0.6193
Alveolar bone loss 0.6884 0.6812 0.4741
Treatments
Prosthodontic treatments 0.0287* 0.0409* 0.0195*
Crown restoration 0.1338 0.4651 0.2265
Resin composite 0.2922 0.2781 0.2668
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Asterisks indicate statistically significant differences, with significance defined as follows: *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001, ****p ≤ 0.0001.

Fig. 4.

Fig. 4

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Associations of significant phenotypic features across clinical diagnoses, genomic regions, and variant types. Bar graphs illustrate the proportion of reported cases exhibiting specific phenotypic features, (A-C) clinically normal permanent dentition, (D-F) severe attrition, (G-I) erosion, (J-L) abrasion, (M-O) enamel deterioration, and (P-R) dentin deterioration, compared across clinical diagnoses, genomic locations within the DSPP gene, and variant types. Each bar represents the total number of reported cases, with coloured segments indicating the number of individuals exhibiting specific phenotypic features. Statistical comparisons between groups were performed using the chi-square test. Statistically significant differences between groups are indicated by distinct letters (a-c) positioned to the right of the bars. Groups with the same letter are not significantly different (p > 0.05), whereas groups with different letters differ significantly (p ≤ 0.05). Bold vertical lines along the right axis denote the group(s) exhibiting the highest proportion of the phenotype.

Fig. 5.

Fig. 5

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Associations of significant phenotypic features across clinical diagnoses, genomic regions, and variant types. Bar graphs illustrate the proportion of reported cases exhibiting specific phenotypic features, (A-C) teeth sensitivity, (D-F) cervical constriction, (G-I) shell teeth, (J-L) pulp exposure, (M-O) pulp obliteration, and (P-R) complete pulp obliteration, compared across clinical diagnoses, genomic locations within the DSPP gene, and variant types. Each bar represents the total number of reported cases, with coloured segments indicating the number of individuals exhibiting specific phenotypic features. Statistical comparisons between groups were performed using the chi-square test. Statistically significant differences between groups are indicated by distinct letters (a-f) positioned to the right of the bars. Groups with the same letter are not significantly different (p > 0.05), whereas groups with different letters differ significantly (p ≤ 0.05). Bold vertical lines along the right axis denote the group(s) exhibiting the highest proportion of the phenotype.

Fig. 6.

Fig. 6

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Associations of significant phenotypic features across clinical diagnoses, genomic regions, and variant types. Bar graphs illustrate the proportion of reported cases exhibiting specific phenotypic features, (A-C) enlarged pulp cavity, (D-F) thistle-shaped pulp chamber, (G-I) pulp stones, (J-L) thin root, and (M-O) prosthodontic treatments, compared across clinical diagnoses, genomic locations within the DSPP gene, and variant types. Each bar represents the total number of reported cases, with coloured segments indicating the number of individuals exhibiting specific phenotypic features. Statistical comparisons between groups were performed using the chi-square test. Statistically significant differences between groups are indicated by distinct letters (a-e) positioned to the right of the bars. Groups with the same letter are not significantly different (p > 0.05), whereas groups with different letters differ significantly (p ≤ 0.05). Bold vertical lines along the right axis denote the group(s) exhibiting the highest proportion of the phenotype.

3.3.1. Milder phenotypes associated with exon 5 frameshift variants and DD-II

Milder phenotypes, characterised by clinically normal permanent dentition and limited structural compromise, were predominantly observed in DD-II (95.45 %) and DD-II/DGI-II (66.67 %) cases. This feature was significantly enriched in individuals with exon 5 variants (49.06 %) and frameshift variants (50 %) (Fig. 4A-C, Supplementary Table 8–10). Similarly, radiographic features like thistle-shaped pulp chambers and pulp stones were predominantly reported in DD-II (72.73 % and 27.27 %, respectively) and were more associated with frameshift variants (Fig. 6D-I, Supplementary Table 8–10).

3.3.2. Severe phenotypes associated with non-exon 5 variants and DGI-III

Severe phenotypes, defined in this review as pronounced structural defects including severe attrition, enamel deterioration, complete pulp obliteration, and pulp exposure, were predominantly associated with non-exon 5 variants and DGI-III. Severe attrition was most prevalent in DGI-III (84.62 %) and was significantly associated with variants in exons 2–3 and with signal peptide cleavage, splice site and missense variants (Fig. 4D-F, Supplementary Table 8–10). The ‘shell teeth’ appearance, a pathognomonic feature of DGI-III (30.77 %), was also more common with variants in exons 2 and 3 and was absent in exon 5 cases (Fig. 5G-I, Supplementary Table 8–10). Pulp exposure, another severe complication, was frequent in DGI-III (38.46 %) and was associated with signal peptide, splice site, and missense variants, but not with frameshift changes (Fig. 5J-L, Supplementary Table 8–10).

3.3.3. Phenotypes with distinct genotypic correlations

Enamel and dentin effects: These phenotypes showed distinct patterns. Enamel deterioration was frequent in DGI-III and non-specified DGI and was strongly linked to variants in exon 2, intron 2, intron 3 and exon 4, as well as signal peptide cleavage, splice site and missense variants (Fig. 4M-O, Supplementary Table 8–10). Dentin deterioration was most associated with variants in exons 3 and 4, and with nonsense variants (Fig. 4P-R, Supplementary Table 8–10).

Pulp obliteration: The pattern of pulp obliteration differed by diagnosis. Complete pulp obliteration was a hallmark of DGI-II (74.47 %), whereas partial pulp obliteration was more common in DD-II and non-specified DGI (Fig. 5M-R, Supplementary Table 8–10).

Regional and variant-specific phenotypes: Notably, tooth sensitivity was a rare finding, reported in only 3 patients, all of whom harboured variants within exon 4 (Fig. 5A-C, Supplementary Table 8–10). Enlarged pulp cavities and thin roots were predominantly associated with exon 4 variants and nonsense variants (Fig. 6A-C, J-L, Supplementary Table 8–10).

3.4. Systemic features and treatment needs

A subset of patients exhibited systemic features. Autosomal dominant non-syndromic hearing loss (DFNA39), characterised by progressive high-frequency sensorineural hearing loss accompanied by DGI, was reported in patients with four different DSPP variants (c.49 C>A, c.52–3 C>G, c.52 G>T, and c.3676delA; Supplementary Table 11). A single case with bone fractures and osteoporosis was associated with the c.3461delG frameshift variant. However, no statistically significant correlation was found between these systemic features and specific diagnoses, locations, or variant types.

Reflecting the severity of the underlying dentin defects, the need for prosthodontic treatments was highest in patients with DGI-III (38.46 %) and those with overlapping DD-II/DGI-II (33.33 %) (Fig. 6M, Supplementary Table 8–10). This need was significantly associated with variants in introns 2–3 and exon 3, and with splice site and missense variants, underscoring the greater clinical burden associated with these genetic alterations (Fig. 6N, O, Supplementary Table 8–10).

4. Discussion

This systematic review synthesises evidence from 48 studies comprising 70 distinct DSPP variants, demonstrating that hereditary dentin defects constitute a continuous, domain-dependent molecular spectrum rather than discrete diagnostic categories. A definitive genotype-phenotype topography emerged: upstream signal peptide and early-region variants drive the profound structural disruption characteristic of DGI-III, whereas downstream exon 5 frameshifts in the DPP domain are associated with the milder DD-II phenotype. Intermediate presentations, particularly DGI-II, were not confined to a specific variant class, suggesting a phenotypic intersection where variable protein toxicity and retention levels overlap. Collectively, these findings refine understanding of the Shields classification, revealing that phenotypic severity is dictated by variant location, the specific domain disrupted, and the resulting burden of intracellular protein retention. This exon-specific gradient provides a conceptual framework to delineate DSPP-related disorders as a genotype-phenotype continuum.

4.1. Molecular mechanisms governing the severity gradient

The non-uniform distribution of variants highlights distinct molecular pathologies. Exon 5, the longest coding region, harbours the majority of variants [24]. Notably, 98 % of the identified variants in exon 5 are frameshift variants, which disrupt the repetitive Asp-Pse-Pse patterns in the DPP region, replacing them with hydrophobic residues such as valine, alanine, and isoleucine, thereby altering the local polarity and hydrophobicity of the protein sequence [25]. Clinically, these variants are strongly associated with DD-II, the mildest form of the spectrum.

The mechanism likely involves a gain-of-function where the hydrophobic mutant protein forms Ca²⁺-dependent aggregates within the rough endoplasmic reticulum (rER), sequestering wild-type DSPP (dominant-negative effect) [26], [27], [28]. It has been proposed that −1 frameshift variants cause partial retention of mutant DSPP within the rER, exerting a dominant-negative effect by formation Ca²⁺-dependent aggregates that sequester wild-type (WT) DSPP and impair its secretion. However, shorter N-terminal frameshifts appear less efficient in promoting aggregate formation or may be expressed at lower levels, thereby permitting residual secretion of functional dentin matrix and leading to the milder clinical manifestation observed in DD-II [29].

Conversely, DGI-III, the most severe clinical form, has not been reported in association with exon 5 variants. Instead, it is primarily linked to alterations in the signal peptide region, splice site, and missense variants within exon 3. Splice site variants situated in introns 2 and 3 and their flanking regions result in exon 3 skipping [30]. The DSPP protein contains a 15-amino-acid signal peptide (MKIITYFCIWAVAWA), followed by the highly conserved IPV motif, which functions as a leader sequence critical for protein trafficking and secretion. This region represents a hotspot for pathogenic variants, as mutations here can disrupt DSPP processing, and retention in the rER, potentially inducing a dominant-negative effect that contributes to severe dentin disorders [31]. Moreover, the apparent missense variant V18F (c.53 T > C, c.53 T > A, and c.53 T > G), when not causing exon 3 skipping, has been shown to maintain properties similar to the IPV motif and results in the mutant protein being retained in the rER [32]. Furthermore, two Dspp-knockin mice models were generated: DsppP19L, corresponding to human p.Pro17Leu, exhibited strong ER retention of DSPP, whereas Dspp−1fs mice displayed reduced ER accumulation. These findings may reflect the milder DD-II phenotype associated with exon 5 variants and the more severe DGI-III phenotype linked to signal peptide, splice site, and IPV motif variants [33].

4.2. DGI-II as a phenotypic intersection

Our analysis confirms that DGI-II was the most frequently reported diagnosis, with causative variants distributed across the entire DSPP gene. This observation, coupled with the significant overlap in diagnoses for identical variants, powerfully underscores the concept that DD and DGI represent a continuous spectrum of disease severity rather than distinct pathological entities [34], [35]. We propose that DGI-II acts as a common phenotypic endpoint that can be reached through a variety of pathogenic mechanisms. For instance, exon 5 frameshift variants may cause DGI-II through a partial dominant-negative effect or haploinsufficiency, while signal peptide or IPV motif variants may produce DGI-II via pronounced ER retention and a stronger dominant-negative mechanism, although with less severity than observed in DGI-III.

Additionally, this variability is frequently confounded by the timing of diagnosis. The hallmark ‘shell teeth’ of DGI-III were most evident in the primary dentition and often transition to a DGI-II-like appearance (pulp obliteration) in permanent teeth as secondary dentin is deposited [30]. Consequently, sporadic cases diagnosed in adulthood are likely to be classified as DGI-II regardless of their underlying genotype [36]. This temporal variability, combined with subjective clinical criteria, underscores the limitations of phenotype-based diagnosis. Integrating DSPP genotyping is therefore essential to distinguish between ‘true’ intermediate phenotypes and age-dependent presentations, ensuring accurate prognosis and appropriate clinical management.

4.3. Systemic features and extra-oral presentations

While DSPP variants are primarily associated with isolated dental defects, specific alleles have been linked to non-syndromic hearing loss (DFNA39). Since the initial report by Xiao et al. [37], sensorineural hearing loss has been described in conjunction with splice site [38] and, less frequently, frameshift variants [39]. Despite these reports, no statistically significant genotype-phenotype correlation has been established, and the precise molecular mechanism linking dentin phosphoprotein defects to auditory function remains unresolved. Additionally, while systemic bone fragility is pathognomonic for DGI-I (associated with COL1A1/COL1A2 variants), rare, atypical presentations have been noted. One case involved a patient with bone fractures and osteoporosis who harboured a DSPP frameshift variant in the absence of identifiable collagen mutations [40]. Although this observation does not definitively establish an etiological role for DSPP in bone physiology, it suggests that the phenotypic spectrum of DSPP-related disorders may be broader than historically recognised or may involve unidentified modifier genes.

4.4. Methodological challenges and the necessity for genomic validation

The historical trajectory of DSPP variant reporting highlights significant challenges in molecular diagnosis, particularly regarding the gene's highly repetitive architecture. Our review identified critical discrepancies in early literature, likely stemming from the limitations of older sequencing technologies and the confounding nature of the polymorphic DPP domain (Exon 5).

Three types of historical errors were noted. First, nomenclature inaccuracies were identified, as early reports often contained mapping mistakes. For example, the variant initially reported as c.3141delC (p.Ser1047fs223) [34] was later corrected to c.3135delC (p.(Ser1045Argfs269)) after alignment with the current reference sequence (NM_014208.3) [41]. Second, misclassification of polymorphisms was observed. Several variants initially considered pathogenic were later reclassified as benign. For example, the c.202 A>T variant, originally implicated in a DGI-II family [42], was subsequently identified in numerous unaffected controls [43], confirming it as a non-pathogenic single-nucleotide polymorphism [44]. Third, true driver variants were occasionally overlooked. The hypervariable nature of the DPP coding region has historically obscured the true causative variants. In one notable case, a DGI-III family was initially thought to carry a compound indel (c.3599_3634del / c.3715_3716ins) within the DPP domain [45]. However, re-evaluation demonstrated that these were benign polymorphisms common in the general population [16], [46]. The true pathogenic driver was later identified as c.49 C>T (p.Pro17Ser) in the signal peptide region [44]. These findings underscore that length variations in the repetitive DPP region must be interpreted with caution. Modern high-throughput sequencing and rigorous variant curation are essential to distinguish true pathogenic variants from benign polymorphisms, ensuring accurate diagnosis and preventing the perpetuation of historical errors in the clinical record.

4.5. Limitations of evidence

The interpretation of these findings requires consideration of several methodological constraints. First, the data were derived primarily from single case reports and small familial series, limiting statistical power and potentially introducing publication bias towards severe or unusual phenotypes. Second, phenotypic characterisation exhibited significant heterogeneity across studies; the lack of standardised reporting led to variable terminology (e.g., ‘DGI-unspecified’), inconsistent radiographic criteria, and subjective thresholds for distinguishing DD-II from DGI-II. Third, genetic methodologies varied substantially, ranging from historical Sanger sequencing of isolated exons to modern high-throughput panels. Consequently, earlier studies may have overlooked deep intronic variants, copy number variations, or regulatory mutations. Furthermore, only a minority of reports included segregation analyses or functional validation, introducing potential uncertainty regarding variant pathogenicity. Despite these limitations, the application of an adapted JBI critical appraisal tool ensured a transparent and rigorous evaluation of the included literature. Future research utilizing standardised phenotypic ontologies and uniform whole-gene sequencing is essential to validate and refine the correlations identified here.

4.6. Towards a genotype-informed diagnostic framework

Synthesising existing evidence with clinical classifications, we propose a phenotype-guided, genotype-informed hybrid framework that complements the established phenotype-based diagnosis of hereditary dentin disorders. This approach retains the Shields classification for initial assessment while integrating molecular findings to enhance prognostic stratification:

  • 1.

    The finding of a frameshift variant in exon 5 should strongly point towards a DD-II diagnosis, particularly if it is in the N-terminal region of the DPP domain. These patients are likely to exhibit clinically normal permanent dentition, thistle-shaped pulp chambers, and a reduced need for prosthodontic intervention.

  • 2.

    Missense or splice site variants affecting the signal peptide or the IPV motif in exons 2–3 should alert the clinician to the possibility of a severe DGI-III phenotype. These patients are at high risk for severe attrition, pulp exposure, and ‘shell teeth’ appearance, and will likely require extensive prosthodontic care.

  • 3.

    The DGI-II phenotype is a genotypically heterogeneous category. It can result from the less severe end of the spectrum of exon 5 frameshifts, from variants in introns 2–3, or from other variant types that cause an intermediate level of protein dysfunction. In these cases, the genetic data provide less prognostic specificity, and clinical monitoring should be comprehensive.

  • 4.

    Variants in exon 4, particularly nonsense variants, appear to be associated with a distinct profile including a high frequency of tooth sensitivity, enlarged pulp cavities, and thin roots, warranting specific clinical attention to these features.

Overall, this hybrid approach supports the continued application of phenotype-based classification for immediate diagnosis and treatment planning. Simultaneously, it leverages genotypic information to enhance risk stratification, anticipate disease progression, and support genetic counseling, thereby refining the management of DSPP-related disorders within a continuous genotype–phenotype spectrum.

4.7. Future perspectives

To advance the understanding of hereditary dentin disorders, future research must transition from isolated case reports to large-scale, longitudinal multi-centre cohorts. Integrating clinical, radiographic, and genomic data will be critical to clarifying the natural history and progression of DSPP-related conditions. Mechanistically, functional validation using CRISPR-edited odontoblast models, tooth organoids, and mineralisation platforms is essential to confirm the diverse pathogenic pathways inferred from human variant data, specifically distinguishing intracellular trafficking defects (DGI-III) and matrix mineralisation impairments (DD-II).

Furthermore, advances in computational biology offer additional opportunities, including machine-learning prediction of variant severity, automated radiographic phenotyping, and integration of molecular dynamics modeling to understand the stability of the DSPP domain. Establishing collaborative international registries of DSPP variants will be pivotal for harmonising diagnostic criteria, reducing reporting variability, and improving variant classification frameworks. These combined efforts will ultimately refine the molecular taxonomy of hereditary dentin defects and accelerate progress towards precision dentistry.

5. Conclusion

This systematic review defines a unified molecular framework for DSPP-related dentin disorders, effectively bridging the diagnostic divide between DD and DGI. Analysis of 70 distinct variants across 48 studies reveals a definitive, exon-dependent severity gradient: upstream signal peptide and splice site variants drive the profound structural failure characteristic of DGI-III, whereas downstream frameshifts within the DPP coding region (exon 5) result in the milder, pulp-specific anomalies of DD-II.

These findings reframe hereditary dentin defects as a continuous genotype–phenotype spectrum rather than a collection of discrete clinical entities. Consequently, the integration of DSPP genotyping into the diagnostic workflow is essential. By identifying variant-specific molecular patterns, clinicians can predict disease severity, distinguish between progressive and stable phenotypes, and implement personalised, evidence-based rehabilitation strategies to optimise long-term oral health.

Declaration of Generative AI and AI-assisted technologies in the writing process

During the preparation of this work, the author used ChatGPT (OpenAI, San Francisco, CA, USA) in order to improve readability and language. After using this tool, the author reviewed and edited the content as needed and takes full responsibility for the content of the published article.

Funding

This project is funded by Thailand Science Research and Innovation Fund Chulalongkorn University (HEA_FF_69_036_3200_003).

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

TP was supported by the Ratchadaphiseksomphot Endowment Fund, Chulalongkorn University (The Exchange Faculty Travel Grant; Grant No. CTG168027). HAR is supported by the Second Century Fund (C2F), Chulalongkorn University. We also acknowledge the C2F, Chulalongkorn University, for supporting the FutureDent Digital Center Project.

Footnotes

Appendix A

Supplementary data associated with this article can be found in the online version at doi:10.1016/j.jdsr.2026.01.001.

Appendix A. Supplementary material

Supplementary material

mmc1.docx (233.2KB, docx)

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Supplementary material

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